Are you over 18 and want to see adult content?
More Annotations
A complete backup of www.veinsensor.pl
Are you over 18 and want to see adult content?
A complete backup of 131458934.keywordblocks.com
Are you over 18 and want to see adult content?
A complete backup of markkavanagh.com
Are you over 18 and want to see adult content?
A complete backup of azscers.000webhostapp.com
Are you over 18 and want to see adult content?
A complete backup of abc12.onesignal.com
Are you over 18 and want to see adult content?
A complete backup of sp-active.adsrvr.org
Are you over 18 and want to see adult content?
A complete backup of services.runescape.com-api.top
Are you over 18 and want to see adult content?
A complete backup of cb1.dev.rtb.owneriq.net
Are you over 18 and want to see adult content?
Favourite Annotations
A complete backup of http://www.elsubtitle.com/title/tt5862312/
Are you over 18 and want to see adult content?
A complete backup of https://x.yump3.ws/descargar-mp3/de-amor
Are you over 18 and want to see adult content?
A complete backup of https://v-s.mobi/qaf-brian-justin-use-somebody-04:06
Are you over 18 and want to see adult content?
A complete backup of https://www.playdaddy.com/newsletter/14/11/index.html
Are you over 18 and want to see adult content?
A complete backup of https://website.informer.com/zaipoc.com
Are you over 18 and want to see adult content?
A complete backup of https://www.kaufmich.com/Dejolie
Are you over 18 and want to see adult content?
A complete backup of https://chinaq.tv/cn191228/1.html
Are you over 18 and want to see adult content?
A complete backup of https://x.yump3.ws/descargar-mp3/arsenal-efectivo
Are you over 18 and want to see adult content?
Text
statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
PUBLICATIONS
A. A. Lee, "Microscopic Mechanism of Thermomolecular Orientation and Polarization", Soft Matter, 12, 8661 (2016) A. A. Lee and S. Perkin, "Ion−Image Interactions and Phase Transition at Electrolyte−Metal Interfaces", Journal of Physical Chemistry Letters, 7, 2753 (2016)TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020.CV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by MansfieldACTIVE MATERIALS
More. Nonequilibrium statistical physics FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
DR ALPHA LEE'S GROUP Aug 2020 Alpha Lee is awarded an University Research Fellowship by the Royal Society Aug 2020 Using techniques in molecular energy landscape analysis, we found that the geometry of loss functions in machine learning seems to exhibit universal features. ALPHA LEE | LEE-GROUP Dr Alpha Lee. I am a Winton Advanced Fellow (Group Leader and Principal Investigator) and a Royal Society University Research Fellow (from Sept 2020) in the Department of Physics, University of Cambridge. My research is broadly speaking in statistical physics and soft condensed matter, with a particular focus on integrating physics,statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
PUBLICATIONS
A. A. Lee, "Microscopic Mechanism of Thermomolecular Orientation and Polarization", Soft Matter, 12, 8661 (2016) A. A. Lee and S. Perkin, "Ion−Image Interactions and Phase Transition at Electrolyte−Metal Interfaces", Journal of Physical Chemistry Letters, 7, 2753 (2016)TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020.CV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by MansfieldACTIVE MATERIALS
More. Nonequilibrium statistical physics FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
ACTIVE MATERIALS
More. Nonequilibrium statistical physicsALUMNI | LEE-GROUP
More. This site was last updated on 24th May 2021PEOPLE | LEE-GROUP
Christmas lunch (2018) This site was last updated on 24th May 2021 DR ALPHA LEE'S GROUP Aug 2020 Alpha Lee is awarded an University Research Fellowship by the Royal Society Aug 2020 Using techniques in molecular energy landscape analysis, we found that the geometry of loss functions in machine learning seems to exhibit universal features. ALPHA LEE | LEE-GROUP Dr Alpha Lee. I am a Winton Advanced Fellow (Group Leader and Principal Investigator) and a Royal Society University Research Fellow (from Sept 2020) in the Department of Physics, University of Cambridge. My research is broadly speaking in statistical physics and soft condensed matter, with a particular focus on integrating physics,statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
PUBLICATIONS
A. A. Lee, "Microscopic Mechanism of Thermomolecular Orientation and Polarization", Soft Matter, 12, 8661 (2016) A. A. Lee and S. Perkin, "Ion−Image Interactions and Phase Transition at Electrolyte−Metal Interfaces", Journal of Physical Chemistry Letters, 7, 2753 (2016)TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
CV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by Mansfield MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020. FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
PEOPLE | LEE-GROUP
Christmas lunch (2018) This site was last updated on 24th May 2021 DR ALPHA LEE'S GROUP Aug 2020 Alpha Lee is awarded an University Research Fellowship by the Royal Society Aug 2020 Using techniques in molecular energy landscape analysis, we found that the geometry of loss functions in machine learning seems to exhibit universal features. ALPHA LEE | LEE-GROUP Dr Alpha Lee. I am a Winton Advanced Fellow (Group Leader and Principal Investigator) and a Royal Society University Research Fellow (from Sept 2020) in the Department of Physics, University of Cambridge. My research is broadly speaking in statistical physics and soft condensed matter, with a particular focus on integrating physics,statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
PUBLICATIONS
A. A. Lee, "Microscopic Mechanism of Thermomolecular Orientation and Polarization", Soft Matter, 12, 8661 (2016) A. A. Lee and S. Perkin, "Ion−Image Interactions and Phase Transition at Electrolyte−Metal Interfaces", Journal of Physical Chemistry Letters, 7, 2753 (2016)TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
CV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by Mansfield MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020. FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
PEOPLE | LEE-GROUP
Christmas lunch (2018) This site was last updated on 24th May 2021ALUMNI | LEE-GROUP
More. This site was last updated on 24th May 2021JOIN US | LEE-GROUP
Thanks for your interest! We are currently looking for PhD students and postdoctoral researchers. Please contact us (alpha@alpha-lee.com) for more information.ACTIVE MATERIALS
More. Nonequilibrium statistical physics DR ALPHA LEE'S GROUP Aug 2020 Alpha Lee is awarded an University Research Fellowship by the Royal Society Aug 2020 Using techniques in molecular energy landscape analysis, we found that the geometry of loss functions in machine learning seems to exhibit universal features. ALPHA LEE | LEE-GROUP Dr Alpha Lee. I am a Winton Advanced Fellow (Group Leader and Principal Investigator) and a Royal Society University Research Fellow (from Sept 2020) in the Department of Physics, University of Cambridge. My research is broadly speaking in statistical physics and soft condensed matter, with a particular focus on integrating physics,statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
PUBLICATIONS
A. A. Lee, "Microscopic Mechanism of Thermomolecular Orientation and Polarization", Soft Matter, 12, 8661 (2016) A. A. Lee and S. Perkin, "Ion−Image Interactions and Phase Transition at Electrolyte−Metal Interfaces", Journal of Physical Chemistry Letters, 7, 2753 (2016)TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
CV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by Mansfield MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020. FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
PEOPLE | LEE-GROUP
Christmas lunch (2018) This site was last updated on 24th May 2021 DR ALPHA LEE'S GROUP Aug 2020 Alpha Lee is awarded an University Research Fellowship by the Royal Society Aug 2020 Using techniques in molecular energy landscape analysis, we found that the geometry of loss functions in machine learning seems to exhibit universal features. ALPHA LEE | LEE-GROUP Dr Alpha Lee. I am a Winton Advanced Fellow (Group Leader and Principal Investigator) and a Royal Society University Research Fellow (from Sept 2020) in the Department of Physics, University of Cambridge. My research is broadly speaking in statistical physics and soft condensed matter, with a particular focus on integrating physics,statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
PUBLICATIONS
A. A. Lee, "Microscopic Mechanism of Thermomolecular Orientation and Polarization", Soft Matter, 12, 8661 (2016) A. A. Lee and S. Perkin, "Ion−Image Interactions and Phase Transition at Electrolyte−Metal Interfaces", Journal of Physical Chemistry Letters, 7, 2753 (2016)TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
CV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by Mansfield MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020. FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
PEOPLE | LEE-GROUP
Christmas lunch (2018) This site was last updated on 24th May 2021ALUMNI | LEE-GROUP
More. This site was last updated on 24th May 2021JOIN US | LEE-GROUP
Thanks for your interest! We are currently looking for PhD students and postdoctoral researchers. Please contact us (alpha@alpha-lee.com) for more information.ACTIVE MATERIALS
More. Nonequilibrium statistical physics DR ALPHA LEE'S GROUP Aug 2020 Alpha Lee is awarded an University Research Fellowship by the Royal Society Aug 2020 Using techniques in molecular energy landscape analysis, we found that the geometry of loss functions in machine learning seems to exhibit universal features. ALPHA LEE | LEE-GROUP Dr Alpha Lee. I am a Winton Advanced Fellow (Group Leader and Principal Investigator) and a Royal Society University Research Fellow (from Sept 2020) in the Department of Physics, University of Cambridge. My research is broadly speaking in statistical physics and soft condensed matter, with a particular focus on integrating physics,statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyCV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by MansfieldDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020.PEOPLE | LEE-GROUP
Christmas lunch (2018) This site was last updated on 24th May 2021 FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
ALUMNI | LEE-GROUP
More. This site was last updated on 24th May 2021 DR ALPHA LEE'S GROUP Aug 2020 Alpha Lee is awarded an University Research Fellowship by the Royal Society Aug 2020 Using techniques in molecular energy landscape analysis, we found that the geometry of loss functions in machine learning seems to exhibit universal features. ALPHA LEE | LEE-GROUP Dr Alpha Lee. I am a Winton Advanced Fellow (Group Leader and Principal Investigator) and a Royal Society University Research Fellow (from Sept 2020) in the Department of Physics, University of Cambridge. My research is broadly speaking in statistical physics and soft condensed matter, with a particular focus on integrating physics,statistics
RESEARCH | LEE-GROUP Research | lee-group. We use physical insights to develop models that can learn from large data sets. Our goal is to discover new materials and drugs. Our work is primarily analytical and computational, although we love interacting with experimental colleagues. Along the way, we develop new statistical techniques to make sense of scientificdata. .
TALKS | LEE-GROUP
2021. Invited e-seminars: . Department of Chemistry EPFL. Randell Centre, Kings College London. Department of Chemistry, Illinois Institute of TechnologyCV | LEE-GROUP
Awards and Prizes. . Fulbright Scholarship (UK-US Fulbright Commission, 2015 -2016) Leathersellers' Company Scholarship, St Catherine's College, Oxford (2013 - 2015) G-Research 1st Prize (University of Oxford, awarded to the top student on the MSc in Mathematical Modelling and Scientitfic Computing, 2013) College Prize (awarded by MansfieldDRUG DISCOVERY
Predicting ligand biological activity is a key challenge in drug discovery. A data-driven approach needs to overcome the challenge that the number of molecules known to be active or inactive is vastly less than the number of possible chemical features that might determine binding. We develop a framework using random matrix theory thatdiscovers
MACHINE LEARNING THEORY We analyze the structure of the loss function landscape of deep neural networks and show why such landscapes are relatively easy to optimize. More generally, our results demonstrate how the methodology developed for exploring molecular energy landscapes can be exploited to extend our understanding of machine learning. PNAS 2020.PEOPLE | LEE-GROUP
Christmas lunch (2018) This site was last updated on 24th May 2021 FLUCTUATING AND DISORDERED MATERIALS The decay of correlations in ionic fluids is a classical problem in soft matter physics that underpins applications ranging from controlling colloidal self-assembly to batteries and supercapacitors. We develop a model that explains the recently observed discontinuous change in the structural force across a thin film of ionicliquid-solvent
ALUMNI | LEE-GROUP
More. This site was last updated on 24th May 2021JOIN US | LEE-GROUP
Thanks for your interest! We are currently looking for PhD students and postdoctoral researchers. Please contact us (alpha@alpha-lee.com) for more information.LEE GROUP
*
Home
*
Alpha Lee
*
People
*
Research
*
Publications
*
Join Us
*
More
THIS SITE WAS LAST UPDATED ON 6TH FEB 2020 STATISTICAL PHYSICS AND PHYSICAL STATISTICS We are a research group in the University of Cambridge. We want to combine science with statistical models to learn from big datasets. PRESS_PICTURE_FOR_ALPHAIONS
1/4
JOIN US
Thanks for your interest! We are currently looking for PhD students and postdoctoral researchers. Please contact us (alpha@alpha-lee.com) for more information.RECENT NEWS
MARCH 2020
Alpha Lee is named Forbes 30 under 30 in Science and Healthcare(Europe)
SEPT 2019
New papers on reaction predictionand
retrosynthesis
featured in TechXplore, Royal Society of Chemistryand Design News
JUL 2019
New paper on Bayesian deep learning for molecular properties prediction published in Chemical ScienceFEB 2019
New paper on random matrix theory and drug discovery published in PNAS and featured in phys.org
Details
Copyright © 2024 ArchiveBay.com. All rights reserved. Terms of Use | Privacy Policy | DMCA | 2021 | Feedback | Advertising | RSS 2.0