Physics of Learning II: Artificial systems
FOCUS · F03 · ID: 46152
Presentations
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Memorizing without overfitting: Over-parameterization in machine learning, physics and biology
ORAL · Invited
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Publication: arXiv:2010.13933, arXiv:2103.14108
Presenters
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Jason W Rocks
Boston University
Authors
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Jason W Rocks
Boston University
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When are Neural Networks Kernel Learners?
ORAL
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Publication: "Neural Networks as Kernel Learners: The Silent Alignment Effect" - in submission. To be on arXiv by late October.
Presenters
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Alexander B Atanasov
Harvard University
Authors
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Alexander B Atanasov
Harvard University
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Blake Bordelon
Harvard University
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Cengiz Pehlevan
Harvard University
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Teaching a material to be adaptive
ORAL
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Presenters
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Martin J Falk
University of Chicago
Authors
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Martin J Falk
University of Chicago
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Jiayi Wu
University of Chicago
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Vedant Sachdeva
University of Chicago
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Sidney R Nagel
University of Chicago
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Arvind Murugan
University of Chicago
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Information theory of high dimensional linear regression
ORAL
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Presenters
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Vudtiwat Ngampruetikorn
The Graduate Center, CUNY, The Graduate Center, City University of New York
Authors
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Vudtiwat Ngampruetikorn
The Graduate Center, CUNY, The Graduate Center, City University of New York
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David J Schwab
The Graduate Center, CUNY
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Learning out of equilibrium in physical systems
ORAL
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Presenters
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Menachem Stern
University of Pennsylvania
Authors
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Menachem Stern
University of Pennsylvania
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Sam J Dillavou
University of Pennsylvania
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Marc Z Miskin
University of Pennsylvania
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Douglas J Durian
University of Pennsylvania
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Andrea J Liu
University of Pennsylvania
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Learning Continuous Chaotic Attractors with a Reservoir Computer
ORAL
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Publication: Lindsay M. Smith, Jason Z. Kim, Zhixin Lu, Danielle S. Bassett. Learning Continuous Chaotic Attractors with a Reservoir Computer. Under Review at Chaos. arXiv: https://arxiv.org/abs/2110.08631
Presenters
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Lindsay M Smith
University of Pennsylvania
Authors
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Lindsay M Smith
University of Pennsylvania
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Jason Z Kim
University of Pennsylvania
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Zhixin Lu
University of Pennsylvania
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Danielle S Bassett
University of Pennsylvania
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Learning Nonequilibrium Control Forces to Characterize Dynamical Phase Transitions
ORAL
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Publication: arXiv preprint arXiv:2107.03348
Presenters
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Jiawei Yan
Stanford University
Authors
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Jiawei Yan
Stanford University
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Hugo Touchette
Stellenbosch University
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Grant M Rotskoff
Stanford Univ
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A Bayesian Approach to Hyperbolic Embeddings
ORAL
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Presenters
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Anoop Praturu
University of California, San Diego
Authors
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Anoop Praturu
University of California, San Diego
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Tatyana O Sharpee
Salk Inst
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A symbolic systen that synthesises an internal model of an algebraic theory of the data and prior knowlwedge
ORAL
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Publication: None
Presenters
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Gonzalo de Polavieja
Centro Champalimaud
Authors
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Gonzalo de Polavieja
Centro Champalimaud
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Optimal learning despite a hundred distracting directions
ORAL
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Presenters
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Michael C Abbott
Yale University
Authors
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Michael C Abbott
Yale University
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Benjamin B Machta
Yale University, Yale
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Memory, Prediction and Computation in the Kuramoto model
ORAL
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Presenters
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Chanin Kumpeerakij
Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Thailand
Authors
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Chanin Kumpeerakij
Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Thailand
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David J Schwab
The Graduate Center, CUNY
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Thiparat Chotibut
Chula Intelligent and Complex Systems Lab, Department of Physics, Chulalongkorn University, Thailand, Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok, Thailand, Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Thailand
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Vudtiwat Ngampruetikorn
The Graduate Center, CUNY, The Graduate Center, City University of New York
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