David J. Schwab

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Pankaj MehtaProfessor, Physics, Boston UniversityVerified email at bu.edu
Gautam AwatramaniUniversity of VictoriaVerified email at uvic.ca
Ari S. MorcosResearch Scientist, Meta AI ResearchVerified email at fb.com
Jonathan FrankleMassachusetts Institute of TechnologyVerified email at mit.edu
DJ StrouseSenior Research Scientist, DeepMindVerified email at google.com
Charles K. FisherUnlearn.aiVerified email at unlearnai.com
Marin BukovSofia UniversityVerified email at phys.uni-sofia.bg
Ching-Hao WangAI/ML at GlaxoSmithKlineVerified email at gsk.com
Edwin Miles StoudenmireResearch Scientist, Flatiron Institute, Center for Computational Quantum PhysicsVerified email at flatironinstitute.org
Thomas GregorInstitut Pasteur and Princeton UniversityVerified email at pasteur.fr
Allyson E. SgroGroup Leader at HHMI's Janelia Research CampusVerified email at janelia.hhmi.org
Ned S. WingreenProfessor of Molecular Biology, Princeton UniversityVerified email at princeton.edu
Ilya NemenmanEmory University, Physics and BiologyVerified email at emory.edu
Barbara TerhalQuTech, TU Delft & Forschungszentrum JuelichVerified email at tudelft.nl
Sudip ChakravartyDepartment of Physics, UCLAVerified email at physics.ucla.edu
Nikolai SlavovNortheastern University, Harvard University, MIT, Princeton UniversityVerified email at fas.harvard.edu
Fred RiekeProfessor, Physiology and Biophysics and HHMI, University of WashingtonVerified email at uw.edu
Arvind MuruganUniversity of ChicagoVerified email at uchicago.edu
Alex H. LangDirector of Perception-Prediction at MotionalVerified email at motional.com
Alex LevineProfessor of Chemistry and Physics, UCLAVerified email at physics.ucla.edu

David J. Schwab

ITS, CUNY Graduate Center

Verified email at gc.cuny.edu - Homepage

Theoretical neuroscience machine learning biophysics


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A high-bias, low-variance introduction to machine learning for physicists P Mehta, M Bukov, CH Wang, AGR Day, C Richardson, CK Fisher, ... Physics reports 810, 1-124, 2019	635	2019
Supervised learning with tensor networks E Stoudenmire, DJ Schwab Advances in Neural Information Processing Systems 29, 2016	365	2016
An exact mapping between the variational renormalization group and deep learning P Mehta, DJ Schwab arXiv preprint arXiv:1410.3831, 2014	280	2014
α-Ketoglutarate coordinates carbon and nitrogen utilization via enzyme I inhibition CD Doucette, DJ Schwab, NS Wingreen, JD Rabinowitz Nature chemical biology 7 (12), 894-901, 2011	219	2011
Energetic costs of cellular computation P Mehta, DJ Schwab Proceedings of the National Academy of Sciences 109 (44), 17978-17982, 2012	205	2012
Atomic Weights and Isotopic Compositions (version 4.1).[Online] Available: http://physics. nist. gov/Comp [2017, March, 20]. National Institute of Standards and Technology JS Coursey, DJ Schwab, JJ Tsai, RA Dragoset Gaithersburg, MD 81, 2015	194*	2015
The deterministic information bottleneck DJ Strouse, DJ Schwab Neural computation 29 (6), 1611-1630, 2017	123	2017
Zipf’s law and criticality in multivariate data without fine-tuning DJ Schwab, I Nemenman, P Mehta Physical review letters 113 (6), 068102, 2014	120	2014
Symmetric extensions of quantum states and local hidden variable theories BM Terhal, AC Doherty, D Schwab Physical review letters 90 (15), 157903, 2003	111	2003
Constant growth rate can be supported by decreasing energy flux and increasing aerobic glycolysis N Slavov, BA Budnik, D Schwab, EM Airoldi, A van Oudenaarden Cell reports 7 (3), 705-714, 2014	87	2014
The early phase of neural network training J Frankle, DJ Schwab, AS Morcos arXiv preprint arXiv:2002.10365, 2020	83	2020
Nonlinear dendritic integration of electrical and chemical synaptic inputs drives fine-scale correlations S Trenholm, AJ McLaughlin, DJ Schwab, MH Turner, RG Smith, F Rieke, ... Nature neuroscience 17 (12), 1759-1766, 2014	74	2014
A central role for mixed acetylcholine/GABA transmission in direction coding in the retina S Sethuramanujam, AJ McLaughlin, G DeRosenroll, A Hoggarth, ... Neuron 90 (6), 1243-1256, 2016	72	2016
X-ray transition energies (version 1.2).[Online] Available: http://physics. nist. gov/XrayTrans [2009, October 20]. National Institute of Standards and Technology RD Deslattes, EG Kessler Jr, P Indelicato, L de Billy, E Lindroth, J Anton, ... Gaithersburg, MD, 2005	71*	2005
From intracellular signaling to population oscillations: bridging size‐and time‐scales in collective behavior AE Sgro, DJ Schwab, J Noorbakhsh, T Mestler, P Mehta, T Gregor Molecular systems biology 11 (1), 779, 2015	65	2015
Lag normalization in an electrically coupled neural network S Trenholm, DJ Schwab, V Balasubramanian, GB Awatramani Nature neuroscience 16 (2), 154-156, 2013	62	2013
Specific wiring of distinct amacrine cells in the directionally selective retinal circuit permits independent coding of direction and size A Hoggarth, AJ McLaughlin, K Ronellenfitch, S Trenholm, R Vasandani, ... Neuron 86 (1), 276-291, 2015	60	2015
Training batchnorm and only batchnorm: On the expressive power of random features in cnns J Frankle, DJ Schwab, AS Morcos arXiv preprint arXiv:2003.00152, 2020	57	2020
Dynamical quorum-sensing in oscillators coupled through an external medium DJ Schwab, A Baetica, P Mehta Physica D: Nonlinear Phenomena 241 (21), 1782-1788, 2012	53	2012
Learning to share and hide intentions using information regularization DJ Strouse, M Kleiman-Weiner, J Tenenbaum, M Botvinick, DJ Schwab Advances in neural information processing systems 31, 2018	48	2018

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