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PIEKNIEWSKI'S BLOG
Intro. Since many of my posts were mostly critical and arguably somewhat cynical , , , at least over the last 2-3 years, I decided to switch gears a little and let my audience know I'm actually a very constructive, busy building stuff most of the time, while my ranting on the blog is mostly a side project to vent, since above everything I'm allergic to naive hype and nonsense. MAY 2021 – PIEKNIEWSKI'S BLOG The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. AI MID 2021. SELF DRIVING CAR MEETS REALITY. Uber and Lyft drivers are here to stay In my previous post I went over the Uber deal with Aurora in which they essentially payed Aurora to take over what was left of the Uber Autonomous car unit. Turns out recently Lyft decided to follow suit and dumped their self driving unit to Toyota.I'm pretty sure Toyota will extract any bits of technology available in this unit to increase the passive ABOUT – PIEKNIEWSKI'S BLOG I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for MLmodels to produce
WHO AM I? – PIEKNIEWSKI'S BLOG As it might be apparent from the content of this blog, I'm interested in AI applied to physical reality in the form of robotics and autonomous behavior. Here is a brief biographical note of whereFILIP PIĘKNIEWSKI
2016 – Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network 2016 – Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback 2010 – Persistent activation blobs in spiking neural networks with mexican hat connectivity – accepted toICAISC 2010.
DEEP LEARNING AND SHALLOW DATA MYTHS AND FACTS ABOUT AI I’m proposing a new machine learning meta-architecture for learning forward models. The architecture is called Predictive Vision Model (PVM).In this blog I present my thoughts on how PVM relates to deep learning and the global AI landscape. AUTOPSY OF A DEEP LEARNING PAPER ELON AND THE COLLECTIVE Elon Musk is a polarizing figure. His ideas frequently come about in casual conversations. People are often amused and impressed by his achievements. I must admit, aPIEKNIEWSKI'S BLOG
Intro. Since many of my posts were mostly critical and arguably somewhat cynical , , , at least over the last 2-3 years, I decided to switch gears a little and let my audience know I'm actually a very constructive, busy building stuff most of the time, while my ranting on the blog is mostly a side project to vent, since above everything I'm allergic to naive hype and nonsense. MAY 2021 – PIEKNIEWSKI'S BLOG The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. AI MID 2021. SELF DRIVING CAR MEETS REALITY. Uber and Lyft drivers are here to stay In my previous post I went over the Uber deal with Aurora in which they essentially payed Aurora to take over what was left of the Uber Autonomous car unit. Turns out recently Lyft decided to follow suit and dumped their self driving unit to Toyota.I'm pretty sure Toyota will extract any bits of technology available in this unit to increase the passive ABOUT – PIEKNIEWSKI'S BLOG I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for MLmodels to produce
WHO AM I? – PIEKNIEWSKI'S BLOG As it might be apparent from the content of this blog, I'm interested in AI applied to physical reality in the form of robotics and autonomous behavior. Here is a brief biographical note of whereFILIP PIĘKNIEWSKI
2016 – Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network 2016 – Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback 2010 – Persistent activation blobs in spiking neural networks with mexican hat connectivity – accepted toICAISC 2010.
DEEP LEARNING AND SHALLOW DATA MYTHS AND FACTS ABOUT AI I’m proposing a new machine learning meta-architecture for learning forward models. The architecture is called Predictive Vision Model (PVM).In this blog I present my thoughts on how PVM relates to deep learning and the global AI landscape. AUTOPSY OF A DEEP LEARNING PAPER ELON AND THE COLLECTIVE Elon Musk is a polarizing figure. His ideas frequently come about in casual conversations. People are often amused and impressed by his achievements. I must admit, a MYTHS AND FACTS ABOUT AI I’m proposing a new machine learning meta-architecture for learning forward models. The architecture is called Predictive Vision Model (PVM).In this blog I present my thoughts on how PVM relates to deep learning and the global AI landscape. AUTONOMOUS VEHICLE SAFETY MYTHS AND FACTS, 2020 UPDATE California DMV disengagements reports are out for 2019, and it is time to plot some data. As usual, these number are not really measuring reliably the safety of AV's and there are plenty ways toMACHINE LEARNING
Intro. Since many of my posts were mostly critical and arguably somewhat cynical , , , at least over the last 2-3 years, I decided to switch gears a little and let my audience know I'm actually a very constructive, busy building stuff most of the time, while my ranting on the blog is mostly a side project to vent, since above everything I'm allergic to naive hype and nonsense. AI – PIEKNIEWSKI'S BLOG It's been 7 months since my last commentary on the field, and as it became regular appearance in this blog (and in fact many people apparently enjoy this form and keep asking for it), it is a time for another one.For those new to the blog, here we generally strip the AI news coverage out of fluff and try to get to the substance, often with a fair dose of sarcasm and cynicism. CIVILIZATION FROM SCRATCH I’m proposing a new machine learning meta-architecture for learning forward models. The architecture is called Predictive Vision Model (PVM).In this blog I present my thoughts on how PVM relates to deep learning and the global AI landscape. DEFLAITION – PIEKNIEWSKI'S BLOG I've started contemplating this post in mid February 2020 while driving back from Phoenix to San Diego, a few miles after passing Yuma, while staring into AI CIRCUS, MID 2019 UPDATE Introduction. It's been roughly a year since I posted my viral "AI winter is well on its way" post and like I promised I'll periodically post an update on the general AI landscape.I posted one some 6 months ago and now is time for another one. And there has been a lot of stuff going on lately and none of it has changed my mind - the AI bubble isbursting.
AUTOPSY OF A DEEP LEARNING PAPER Introduction. I read a lot of deep learning papers, typically a few/week. I've read probably several thousands of papers. My general problem with papers in machine learning or deep learning is that often they sit in some strange no man's land between science andengineering, I
A BRIEF STORY OF SILICON VALLEY’S AFFAIR WITH AI Once upon a time, in the 1980's there was a magical place called Silicon Valley. Wonderful things were about to happen there and many people were about make a ton of money. These things werePIEKNIEWSKI'S BLOG
Intro. Since many of my posts were mostly critical and arguably somewhat cynical , , , at least over the last 2-3 years, I decided to switch gears a little and let my audience know I'm actually a very constructive, busy building stuff most of the time, while my ranting on the blog is mostly a side project to vent, since above everything I'm allergic to naive hype and nonsense.PIEKNIEWSKI'S BLOG
Piekniewski's blog – On limits of deep learning and where to go next with AI. Ai mid 2021. Self driving car meets reality. The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. AI MID 2021. SELF DRIVING CAR MEETS REALITY. Ai mid 2021. Self driving car meets reality. The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. Some of them very well predicted by articles in this blog, and some surprising. MAY 2021 – PIEKNIEWSKI'S BLOG The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. ABOUT – PIEKNIEWSKI'S BLOG About. I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for ML models to produce true understanding of physical reality. My recent attempt to build a machine learning system thatnaturally
WHO AM I? – PIEKNIEWSKI'S BLOG Here is a brief biographical note of where that came from and what I did so far. This is meant to help understand where I'm coming from and why I believe what I believe. My adventure with AI started in late 90's. While still in high school I started attending some lectures in my hometown Torun (Poland). These lectures were given by Wlodek DuchFILIP PIĘKNIEWSKI
Filip Piękniewski, PhD. San Diego, CA. e-mail: Polish Version. I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for AUTONOMOUS VEHICLE SAFETY MYTHS AND FACTS, 2020 UPDATE Autonomous vehicle safety myths and facts, 2020 update. Posted March 1, 2020. March 1, 2020. by Filip Piekniewski. California DMV disengagements reports are out for 2019, and it is time to plot some data. As usual, these number are not really measuring reliably the safety of AV's and there are plenty ways to game them, or overreport. DEEP LEARNING AND SHALLOW DATA AI CIRCUS, MID 2019 UPDATE ELON AND THE COLLECTIVE Elon and the collective. Posted December 28, 2018. January 12, 2019. by Filip Piekniewski. Elon Musk is a polarizing figure. His ideas frequently come about in casual conversations. People are often amused and impressed by his achievements. I must admit, a few years back I thought he is literally the next Steve Jobs, only actually better,since
PIEKNIEWSKI'S BLOG
Piekniewski's blog – On limits of deep learning and where to go next with AI. Ai mid 2021. Self driving car meets reality. The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. AI MID 2021. SELF DRIVING CAR MEETS REALITY. Ai mid 2021. Self driving car meets reality. The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. Some of them very well predicted by articles in this blog, and some surprising. MAY 2021 – PIEKNIEWSKI'S BLOG The pandemic has largely overwhelmed the news cycle over the past year and hence influencing and largely deflating the AI hype train. There were a few developments though which I'd consider significant. ABOUT – PIEKNIEWSKI'S BLOG About. I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for ML models to produce true understanding of physical reality. My recent attempt to build a machine learning system thatnaturally
WHO AM I? – PIEKNIEWSKI'S BLOG Here is a brief biographical note of where that came from and what I did so far. This is meant to help understand where I'm coming from and why I believe what I believe. My adventure with AI started in late 90's. While still in high school I started attending some lectures in my hometown Torun (Poland). These lectures were given by Wlodek DuchFILIP PIĘKNIEWSKI
Filip Piękniewski, PhD. San Diego, CA. e-mail: Polish Version. I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for AUTONOMOUS VEHICLE SAFETY MYTHS AND FACTS, 2020 UPDATE Autonomous vehicle safety myths and facts, 2020 update. Posted March 1, 2020. March 1, 2020. by Filip Piekniewski. California DMV disengagements reports are out for 2019, and it is time to plot some data. As usual, these number are not really measuring reliably the safety of AV's and there are plenty ways to game them, or overreport. DEEP LEARNING AND SHALLOW DATA AI CIRCUS, MID 2019 UPDATE ELON AND THE COLLECTIVE Elon and the collective. Posted December 28, 2018. January 12, 2019. by Filip Piekniewski. Elon Musk is a polarizing figure. His ideas frequently come about in casual conversations. People are often amused and impressed by his achievements. I must admit, a few years back I thought he is literally the next Steve Jobs, only actually better,since
FILIP PIĘKNIEWSKI
Filip Piękniewski, PhD. San Diego, CA. e-mail: Polish Version. I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for MYTHS AND FACTS ABOUT AI Some of the current AI algorithms draw loosely from the neuroscience of the late 1970's (e.g. the concept of the neocognitron). Since then neuroscience did make a few discoveries which generally did not reveal how the brain works, but certainly showed that it does not work the way we thought earlier. Therefore to summarise: we don't know howMACHINE LEARNING
Intro. Since many of my posts were mostly critical and arguably somewhat cynical , , , at least over the last 2-3 years, I decided to switch gears a little and let my audience know I'm actually a very constructive, busy building stuff most of the time, while my ranting on the blog is mostly a side project to vent, since above everything I'm allergic to naive hype and nonsense. CIVILIZATION FROM SCRATCH Civilization from scratch. Posted July 26, 2019. July 26, 2019. by Filip Piekniewski. This post is not about AI and not about winter. I have a few of those coming, but this one is about something different. I hope you don't mind. A friend of mine recently gave a lot to think about by stating the following thought experiment: AI CIRCUS, MID 2019 UPDATE Introduction. It's been roughly a year since I posted my viral "AI winter is well on its way" post and like I promised I'll periodically post an update on the general AI landscape.I posted one some 6 months ago and now is time for another one. And there has been a lot of stuff going on lately and none of it has changed my mind - the AI bubble isbursting.
AUTOPSY OF A DEEP LEARNING PAPER The central point of an engineering paper is an application, and the rest is just a collection of ideas that allow to solve the application. Machine learning sits somewhere in between. There are examples of clear scientific papers (such as e.g. the paper that introduced the backprop itself) and there are examples of clearlyengineering papers
A BRIEF STORY OF SILICON VALLEY’S AFFAIR WITH AI A brief story of Silicon Valley's affair with AI. Once upon a time, in the 1980's there was a magical place called Silicon Valley. Wonderful things were about to happen there and many people were about make a ton of money. These things were all related to the miracle of a computer and how it would revolutionize pretty much everything. CAN A DEEP NET SEE A CAT? January 12, 2017. by Filip Piekniewski. In this post I will explore the capabilities of contemporary deep learning models on the vitally important task of detecting a cat. Not an ordinary cat though, but a sketch of an abstract cat. This task matters because success tells us something about whether a visual system has learned generalization and AI WINTER – ADDENDUM – PIEKNIEWSKI'S BLOG AI winter - Addendum. Posted June 6, 2018. June 19, 2018. by Filip Piekniewski. My previous post on AI winter went viral almost to the point of killing my Amazon instance (it got well north of 100k views). It triggered a serious tweet storms, lots of discussion on hackernews and reddit. From this empirical evidence one thing is clear - whether AI WINTER IS WELL ON ITS WAY AI winter is well on its way. Deep learning has been at the forefront of the so called AI revolution for quite a few years now, and many people had believed that it is the silver bullet that will take us to the world of wonders of technological singularity (general AI). Many bets were made in 2014, 2015 and 2016 when still new boundaries wereHOME PAGE
Filip Piękniewski, PhDSAN DIEGO, CA
e-mail:
Polish Version
I’m a researcher working on computer vision and AI. My main research objective is to introduce dynamics into machine learning which is currently dominated by statistics. Having dynamics is necessary for ML models to produce true understanding of physical reality. My recent attempt to build a machine learning system that naturally incorporates time, online processing and unsupervised learning of the physics is described here (github code here ). Until dynamics is deeply incorporated in machine learning models, they will remain “statistical machines” that “statistically work” which is not enough for a real world application such as robotics. My long term ambition is to address Moravec’s Paradox. You may read more
in my blog on machine learning and other things.
Research
My research interestsRecent research activitiesPublicationsPatents * Computer Science in general * Computational Intelligence * Neural networks (deep learning in current lingo) * Random graphs and small world networks * Hopfield networks, phase diagrams * Critical phenomena * Spiking Neural Networks* Texture analysis
* Dynamic systems and fractals * Information theory * Computer modeling/GPU programming * UNIX/Linux/MacOSX administration * Creating a large scale predictive vision model incorporatingfeedback
* Analysis of network topologies emerging from spiking neural models and other simplified computational models * Study of critical systems * 2016 – Unsupervised Learning from Continuous Video in a Scalable Predictive Recurrent Network * 2016 – Fundamental principles of cortical computation: unsupervised learning with prediction, compression and feedback * 2010 – Persistent activation blobs in spiking neural networks with mexican hat connectivity–
accepted to ICAISC 2010 . Supplemental matlabscript
and movie 1
, movie
2 .
* 2010 – Spectra of the Spike Flow Graphs of Recurrent NeuralNetworks
–
presentation for the ICANN conference. * 2010 – Theoretical model for mesoscopic-level scale-free self-organization of functional brain networks,
preprint submitted to IEEE TNN (BiBTeX)
* 2009 – Spectra of the Spike Flow Graphs of Recurrent NeuralNetworks
preprint
submitted to ICANN (BiBTeX)
* 2009 – Robustness of Power Laws in Degree Distributions for Spiking Neural Networkspreprint
submitted to IJCNN 2009. BiBTeX * 2008 – PhD thesis–
defended on April 1st 2009 at Warsaw University. * 2008 – Spontaneous Scale-free Structure of Spike Flow Graphs in Recurrent Neural Networks, preprint
submitted to Neural Networks (BiBTeX)
* 2007 – Emergence of Scale-Free Graphs in Dynamical SpikingNeural Networks
, a poster
presented at 2007 International Joint Conference on Neural Networks, Orlando 2007 (BiBTeX)
* 2007 – Emergence of Scale-Free Graphs in Dynamical SpikingNeural Networks
, 2007
International Joint Conference on Neural Networks, Orlando 2007(BiBTeX )
* 2007 – Emergence of Scale-Free Spike Flow Graphs in RecurrentNeural Networks
,
2007 IEEE Symposium on Foundations of Computational Intelligence, Honolulu Hawai 1-5 April 2007 (BiBTeX)
* 2006 – Mesoscopic Approach to Locally Hopfield Neural Networks in Presence of Correlated Patterns, 2006
International Joint Conference on Neural Networks, Vancouver, BC, Canada July 16-21, 2006, pp 5899 (BiBTeX)
* 2005 – Phase diagrams for locally Hopfield neural networks in presence of correlated patterns,Proceedings
of International Joint Conference on Neural Networks, Montreal, Canada, July 31 – August 4, 2005, pp 776 (BiBTeX)
* 2004 – Visualizing and Analyzing Multidimensional Output from MLP Networks via Barycentric Projections,
Springer-Verlag, Lecture Notes on Artificial Inteligence vol 3070(BiBTeX )
* 2004 – Visual comparison of performance for different activation functions in MLP networks,
Proceedings of Internartional Joint Conference on Neural Networks, Budapest, Hungary 2004, pp 2947-2953. (BiBTeX)
* Check my google scholar pagefor citations
* Sensory input processing apparatus in a spiking neural networkPiekniewski, F.,
Izhikevich, E., Szatmary, B., & Petre, C. (2012). _U.S. Patent Application 13/465,903_. * Spiking neural network object recognition apparatus and methodsPiekniewski, F.,
Izhikevich, E., Szatmary, B., & Petre, C. (2012). _U.S. Patent Application 13/465,918_. * Spiking neural network feedback apparatus and methodsPiekniewski, F.,
Izhikevich, E., Szatmary, B., & Petre, C. (2012). _U.S. Patent Application 13/465,924_. * ELEMENTARY NETWORK DESCRIPTION FOR EFFICIENT IMPLEMENTATION OF EVENT-TRIGGERED PLASTICITY RULES IN NEUROMORPHIC SYSTEMSIzhikevich, E.
M., Szatmary, B., Petre, C., Piekniewski, F., & Nageswaran, J. M. (2013). _U.S. Patent No. 20,130,073,492_. Washington, DC: U.S. Patent and Trademark Office. * ELEMENTARY NETWORK DESCRIPTION FOR EFFICIENT MEMORY MANAGEMENT IN NEUROMORPHIC SYSTEMSIzhikevich,
E. M., Szatmary, B., Petre, C., & Piekniewski, F. (2013). _U.S. Patent No. 20,130,073,484_. Washington, DC: U.S. Patent and TrademarkOffice.
* ELEMENTARY NETWORK DESCRIPTION FOR NEUROMORPHIC SYSTEMSIzhikevich, E.
M., Szatmary, B., Petre, C., Nageswaran, J. M., & Piekniewski, F. (2013). _U.S. Patent No. 20,130,073,495_. Washington, DC: U.S. Patent and Trademark Office. * ELEMENTARY NETWORK DESCRIPTION FOR EFFICIENT LINK BETWEEN NEURONAL MODELS AND NEUROMORPHIC SYSTEMSIzhikevich, E.
M., Petre, C., Piekniewski, F., & Szatmary, B. (2013). _U.S. Patent No. 20,130,073,498_. Washington, DC: U.S. Patent and Trademark Office. * APPARATUS AND METHOD FOR PARTIAL EVALUATION OF SYNAPTIC UPDATES BASED ON SYSTEM EVENTSIzhikevich, E.
M., Piekniewski, F., & Nageswaran, J. M. (2013). _U.S. Patent No. 20,130,073,499_. Washington, DC: U.S. Patent and Trademark Office. * APPARATUS AND METHODS FOR SYNAPTIC UPDATE IN A PULSE-CODED NETWORKIzhikevich, E.
M., Piekniewski, F., & Nageswaran, J. M. (2013). _U.S. Patent No. 20,130,073,491_. Washington, DC: U.S. Patent and Trademark Office. * APPARATUS AND METHODS FOR TEMPORALLY PROXIMATE OBJECT RECOGNITIONPiekniewski, F.
L., Petre, C., Sokol, S. H., Szatmary, B., Nageswaran, J. M., & Izhikevich, E. M. (2012). _U.S. Patent No. 20,120,308,076_. Washington, DC: U.S. Patent and Trademark Office. * APPARATUS AND METHODS FOR TEMPORALLY PROXIMATE OBJECT RECOGNITIONPIEKNIEWSKI, F.,
PETRE, C., SOKOL, S., SZATMARY, B., NAGESWARAN, J., & IZHIKEVICH, E. (2012). _WIPO Patent No. 2012167164_. Geneva, Switzerland: World Intellectual Property Organization. * APPARATUS AND METHODS FOR SYNAPTIC UPDATE IN A PULSE-CODED NETWORKIZHIKEVICH, E.,
PIEKNIEWSKI, F., & NAGESWARAN, J. (2013). _WIPO Patent No. 2013043903_. Geneva, Switzerland: World Intellectual PropertyOrganization.
* ELEMENTARY NETWORK DESCRIPTION FOR NEUROMORPHIC SYSTEMSIZHIKEVICH, E.
M., SZATMARY, B., PETRE, C., NAGESWARAN, J. M., & PIEKNIEWSKI, F. (2013). _WIPO Patent No. 2013043610_. Geneva, Switzerland: World Intellectual Property Organization. * More submitted, check my google scholar pageTeaching
20132009/2010
SPIKING NEURAL NETWORKS AS A PARALLEL COMPUTING PARADIGM June 2013, six lectures at Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Toruń* Lecture notes
MATHEMATICAL FOUNDATIONS OF NEUROSCIENCE – winter semester 2009/2010. Preliminary program.Any
supplemental material will be published here. Lecture presentations:* Lecture 1
– Basic
facts about the brain and its analysis, Sample questions* Lecture 2
–
Electrophysiology of neurons, Sample questions* Lecture 3
–
Electrophysiology of neurons (continued), Sample questions* Lecture 4
– 1d
systems, Sample questions* Lecture 5
– 2d
systems, Sample questions* Lecture 6
–
Bifurcations in 2d systems, Sample questions* Lecture 7
–
Bifurcations II, Sample questions* Lecture 8
–
Classes of excitability, Sample questions* Lecture 9
–
Simple models of neurons and synapses, Sample questions* Lecture 10
–
Bursting, Sample questions* Lecture 11
–
Bursting continued Sample questions* Lecture 12
–
Synchronization Sample questions* Lecture 13
–
Coupled Oscillators Sample questions* Lecture 14
–
Synchronization of neurons and synaptic plasticity Sample questions* Lecture 15
–
Building large models step by step Sample questions Programs/scripts/animations: * DTI tracking with Slicer 3d– a
QuickTime animation
* Slicer3d program webpage – an opensource medical visualization software. Also check the tutorialswhich
include the nescessary data files. * Numerical stability demo–
Matlab/Octave script * Saddle node bifurcation of a 1d system–
Matlab/Octave script * Quadratic integrate and fire neuron–
Matlab/Octave script * Saddle-node bifurcation in 1d system–
a QuickTime animation * Saddle-node on invariant cicrle bifurcation in the Na-p-K model– a
QuickTime animation
* Phase portrait plot–
Matlab/Octave script and sample fields to plot: sample fieldimage)
, sample
field 2
image)
, sample
field 3
image)
, sample
field 4
image)
* Fold Cycle bifurcation in the canonical model–
a QuickTime animation * Saddle Homoclinic Orbit bifurcation in the Na-p-K model–
a QuickTime animation * Supercritical Andronov-Hopf bifurcation in the Na-p-K model–
a QuickTime animation * Subcritical Andronov-Hopf bifurcation in the Na-p-K model–
a QuickTime animation * Saddle node bifurcation in the Na-p-K model–
a QuickTime animation * Dynamic regimes near Bogdanov-Takens bifurcation–
a QuickTime animation * A script simulating an array of coupled neurons – good studentproject seed
–
Matlab/Octave script * Lecture notes of Georgi Medvedev, useful supplementary material * Publications of Eugene Izhikevich, useful supplementary material * A script simulating a piece of an axon with the cable equation – good student project seed–
Matlab/Octave script * An animation of an action potential propagating spatialy along thefiber – a
QuickTime animation
* Spiking Neuron Models Single Neurons, Populations, Plasticity a book by Wulfram Gerstner and Werner M. Kistler – useful supplementary material * A script simulating a piece of an axon with the cable equation (FitzHugh-Nagumo) – good student project seed–
Matlab/Octave script * A spiking network with CUDA – A project by Jayram Moorkanikara Nageswaran et.al* Hysteresis loop
– a
QuickTime animation
* Hysteresis loop
–
Matlab/Octave script * INa-IK-IK(M) burster–
Matlab/Octave script * An animation of an action potential propagating spatialy along the fiber in a bursting model (fold/homoclinic bursting)–
a QuickTime animation * An animation of an action potential propagating spatialy along the fiber in a bursting model (circle/circle bursting)–
a QuickTime animation * INa-IK-IK(M) circle/circle burster spatial solution–
Matlab/Octave script * A mesh resembling a neuron in 3d–
Blender file
* Another mesh resembling a neuron in 3d–
Blender file
* INa-IK-IK(M) Fold/Homoclinic burster spatial solution–
Matlab/Octave script * Propagating Waves in Neocortical SlicesResearch
results of JIAN-YOUNG WU, PH.D. * Some more movies ofJian-Young Wu
* Okinawa computational neuroscience course – a very good summer school, I encourage my students to apply! * Neuron – software for neuronsimulations
* Web page of Bard Ermentrout an author of XPP and many publications on mathematical neuroscience * Solution of a bursting neuron in 2d– note
the artifacts related to the second order derrivative mask * Solution of a bursting neuron in 2d (source)–
Matlab/Octave script * Rotating waves in a grid of coupled oscillators– a
QuickTime animation
* Spiral waves in a grid of coupled oscillators–
a QuickTime animation * 2d grid of coupled oscillators (source)–
Matlab/Octave script* Computing PRC
–
Matlab/Octave script * Poincare phase map–
Matlab/Octave script Selected student projects: * Multi compartment neuron modelRafal Malkowski
* NiC (Neurons in CUDA)Michal Matuszak
* 3D Neuron Model Bartosz Paprzycki * Persistent sodium and potassium neuron modelJaroslaw
Piersa
* Neurotest AndrzejRutkowski
* Neurons in flash BartoszZielinski
* The Hodgkin-Huxley model – action potentialMarcin
Duchinski
Other stuff
Some minor projectsInteresting links * Mixed photos from San Diego area, 2010,2011 * A movie related to Brain Corporation shown by PBS * Milky Way time lapsemovie taken on
14 Dec 2010 on Mt Laguna, some meteors are visible too, mov* Mysterious e
a
presentation for high school, Swiecie 2009, polish pdf * Scale-free networksa presentation
on a seminar, polish pdf * Digital Signal Processinga
presentation for high school students, polish pdf * Signal and image processing algorithmsa presentation
on a seminar, polish pdf * Inside the Menger Spongea ptviewer
360 panorama inside this exciting shape * Scale free structures in recurrent neural networksa presentation on
a seminar, polish pdf * A Beamer theme with my Faculty colors and university logos * Finding roots using binary or interpolation searcha
demonstration I made in Mathematica for Wolfram Demonstrations Project * Cayley Trees in Mathematicaa demonstration I
made in Mathematica for Wolfram Demonstrations Project * Map of Computer Sciencegraphical
representation of areas in computer science and relations betweenthem, english pdf
* Expander graphs and their applicationsa presentation
on a seminar, polish pdf * A couple of pics of Torun in HSIRpictures
with V (value) channel replaced by infrared image, nice effect * Magia algorytmów obróbki obrazua
presentation for annual science and art festival about digital photography and image processing (polish, html) * My faculty yard via PTviewer a 360 degree panorama of a yard at my faculty * Fractals with Maplea set of Maple
procedures used to plot a number of fractals * My infrared photographsa couple of
compositions done with Hoya R72 filter and olympus C7070 * 2d Lattice of Simplified Dynamical Neuronsstudent
project for OCNC 2006 (english, mov) * Losowosc w informatycea presentation
for annual science and art festival in Torun (polish, pdf)* WLAN safety
– a
presentation that I commited for the eduroam semminar in march 2006 (polish, pdf).* Torun in my lens
– a web
gallery containing some photos of my hometown that I collected inrecent years.
* Analiza stabilności i diagramów fazowych dla lokalnie hopfieldowskich sieci neuronowych w obecności wysoce skorelowanychwzorców okresowych
– My masters thesis(Polish pdf)
* CS in Education 2005 Conference – Arythmetic routines in Pascaland C++ –
materials for workshops (polish html) * Samba and LDAP Howto– useful
howto on ldap authorization in samba (Polish pdf) * Real Video Streaming Howto– useful
howto on real video streaming (Polish pdf)* Fractals
–
Presentation for science festival about fractals (Polish HTML!!! <-NEW )
* Fractals –
Presentation for science festival about fractals (Polish pdf) * SIMP documentation–
Technical aspects of the project that my team has written, and won departamets team programming contest ‘2004 (Polish pdf). * Gamma tranformations– Short
thesis about gamma transformations of digital images (Polish pdf).* Java project
– A small java
applet for demonstration of Kohonen Self Organizing Map (neuralnetwork method).
* Eugene M. Izhikevich web page – a mathematician involved into study of brain function and itssimulation.
* Steve Furber
– developer of
the ARM chip, involved into the SpiNNakerproject (a
parallel chip designed to run neurosimulations) * Scholarpedia – a peer reviewed version of wikipedia. * Computational Cognitive Neuroscience Laboratory Indiana University Bloomington * prof. Dante R. Chialvo – author of interesting neuroscience research related to my work * racjonalista.pl – polish sitefor rational people
* slashdot.org – web magazine for those with open minds (well, those that dont mind being a bitAmerica-centric).
* meteo.icm.edu.pl – good numeric weather forecast for central Europe * mathworld.woflram.com – online encyclopedia of mathematics * citeseer.com – Scientific literaturedigital library
* Prof. W. Duch webpage – An AI specialist, this page is a gold mine. * Leszek Rybicki – the page of my friend and coauthor of some the projects. * Agata Piekniewska – thepage of my wife.
* Airbrush studio R if you need a fancy painting on your car! * E. Dyguda page – Nice page of a young researcher who likes Linux. * WMiI – The departament that Istudy in
* PTI – Polish Information Processing Society (Koło Toruńskie Polskiego Towarzystwa Informatycznego), a society that I’m an active member. * www.subaqua.pl – A web page that I’ve designed for my favourite diving club. * Wysokie progi – Polish/American hiking club in Southern California. * eduroam.umk.pl – Worldwide safe Wifi project, that I participated in 2005r. Photos from journeys/conferences etc. Some of the galleries may take a few minutes to load, depending on the Internet connection speed. Enjoy!* 2018
* Valley of Fire, Nevada, November 2018 * Grand Canyon, North Rim, Arizona, August 2018 * Yellowstone NP, Wyoming, August 2018 * Grant Teton NP, Wyoming, August 2018 * Sierra Nevada, Big Pine California, July 2018* 2017
* Valley of Fire – Nevada, November 2017 * Death Valley, Las Vegas, Zion + Bryce + Antelope Canyon + Grand Canyon – October 2017 * Total Solar Eclipse – August 2017, Oregon * ICML Sydney Australia, August 2017* 2016
* Death Valley, Racetrack Playa, November 2016 * Pinnacles NP and Big Sur, April 2016* 2015
* Yosemite & Sequoia, December 2015 * Anza Borrego camping, April 2015 * Algodones Dunes, near Yuma, California, March 2015 * Seguaro National Park, Tucson, Arizona, March 2015 * Biosphere2, Arizona, March 2015 * Page, Arizona, March 2015 * Snowbird, Utah, March 2015 * Salt Lake, Antelope Island, Utah, March 2015 * Zion, Utah, March 2015 * Salvation Mountain, California, February 2015* 2014
* San Felipe, Baja California, Mexico, May 2014 * Yosemite, Lake Mono and Mt Whitney Portal, California, May 2014* 2013
* Joshua Tree, California, December 2013 * Grand Canyon, Arizona, December 2013 * Monument Valley, Utah/Arizona, December 2013 * Arches, Utah, December 2013 * Canyonlands, Utah, December 2013 * Bryce Canyon, Utah, December 2013 * Zion, Utah, December 2013 * Death Valley, California, November 2013 * Organisation for Computational Neurosciences meeting, Paris,France, July 2013
* Sequoia and Kings Canyon National Parks, July 2013 * COSYNE conference and workshops, Salt Lake City and Snowbird, Utah2013
* 2012
* Society for Neuroscience Meeting, New Orleans LA, October 2012 * COSYNE conference and workshops, Salt Lake City and Snowbird, Utah2012
* 2011
* Society for Neuroscience Meeting, Washington DC, November 2011 * Hiking in Anza Borrego desert, November 2011 * COSYNE conference and workshops, Salt Lake City and Snowbird, Utah2011
* Mammoth Lakes CA, January 2011* 2010
* Hawaii, November 2010 * MCAS Miramar Airshow, San Diego, October 2010 * NVIDIA GPU Technology Conference, San Jose CA + San Francisco and Silicon Valley, September 2010 * Arizona, September 2010 * ICAISC conference, Zakopane, Poland, June 2010 * Vision Science Society Meeting, Naples, Florida, May 2010 * Los Angeles, Hollywood, Malibu, Santa Monica, April 2010* San Diego, 2010
* 2009
* ICANN conference Limassol Cyprus, September 2009 * IJCNN conference Atlanta, GA, June 2009 * ICCNS conference Boston, MA, May 2009* Egypt, May 2009
* 2007
* IJCNN Orlando, Florida , August, 2007 * A couple of hours in Washington between the flights on the way to Orlando, August, 2007 * A couple of hours in San Francisco, California, April 2007 * IEEE-SSCI Honolulu, Hawaii, April 2007* 2006
* London, UK, November 2006 * Nashville Tennessee, August 2006 * Las Vegas, Hoover Dam and Grand Canyon, August 2006 * Denver Colorado and Rocky Mountains hiking, July 2006 * Whistler mountain hiking, Whistler BC Canada, July 2006 * World Congress on Computational Intelligence, Vancouver BC Canada,July 2006
* Two days in Tokyo, Japan, July 2006 * Okinawa Computational Neuroscience Course – Okinawa, Japan, June2006
* Stochastic Models in Biological Sciences Workshop – Warsaw,Poland, May 2006
* Ice diving in Powidzkie lake in Poland, February 2006 * Polish Information Processing Society awards, Wroclaw, PolandFebruary 2006
* 2005
* Diving safari, st. Jones reef, Egypt, October 2005 * Cappadocia, hot air balloon flight, Turkey, September 2005 * Journey round Turkey (Fethiye, Pergamon, Istambul), September 2005 * Philadelphia, August 2005 * New York, August 2005 * Harpers Ferry, West Virginia, August 2005 * Baltimore, Annapolis – Maryland, August 2005 * Washington DC, July-August 2005 * Montreal and Quebeck City, July 2005, IJCNN conference * Departament of Informatics Workshop in Bachotek – May 2005 * Ice diving in Kamionki lake near Torun – February 2005* 2004
* Diving trip to Dahab (Egypt) – November 2004 * Eighth national meeting of amateur astronomers (OZMA), Niedzwiady– August 2004
* IJCNN Conference, Budapest – July 2004 * ICAISC conference, Zakopane – June 2004 * Diving trip to Egypt (Sharm el Sheikh) – April 2004* 2003
* PTI picnic in Bachotek – May 2003 * Journey to Egypt (Hurghada) – January 2003 Bright stars shine briefly - memory of a friend who died too earlyTOMASZ
SCHREIBER, my scientific advisor, collaborator, coauthor, friend. We started working together in 2003, at that time he was already a rising star of polish mathematics. Working with him was always a pleasure. Tomek was a kind of man who had been giving the best, never asking for anything in exchange. Always smiling, full of energy, full of faith in people. He was incredibly bright, with a great sense of humor. He could play with mathematical symbols so cleverly that it sometimes took a few days to understand what he achieved in seconds. When a few years ago Tomek was mourning his advisor, Alexander Nagaev who died in a tragic accident I could not imagine that I’ll be mourning him so soon. In recent years he has been fighting with a fatal disease. But the disease was never an excuse for him. Instead it was something that motivated him to an even harder work. He died on first of December 2010. He was 35. He left his wife, loving family, great students and friends, tens of unfinished mathematical ideas. I will always rememberhim smiling.
Tomasz Schreiber’s Memorial Session My memories of Tomek (c) Filip Piekniewski 2013Details
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