Inference, Information, and Learning in Biophysics: I

Presentations

• What can and can't Machine Learning do for Physics?

  Invited

  March 4, 2020, 4:30 PM – March 4, 2020, 5:06 PM

  Presenters

  • Pankaj Mehta

    Boston Univ, Physics, Boston Univ, Boston University

  Authors

  • Pankaj Mehta

    Boston Univ, Physics, Boston Univ, Boston University

  View abstract →

• Coarse scale representation of spiking neural networks: from dynamics to backpropagation through spikes

  ORAL

  March 4, 2020, 5:06 PM – March 4, 2020, 5:18 PM

  Presenters

  • Angel Yanguas-Gil

    Argonne National Laboratory

  Authors

  • Angel Yanguas-Gil

    Argonne National Laboratory

  View abstract →

• Towards a grammar of probabilistic models for large biological networks

  ORAL

  March 4, 2020, 5:18 PM – March 4, 2020, 5:30 PM

  Presenters

  • Philipp Fleig

    University of Pennsylvania

  Authors

  • Philipp Fleig

    University of Pennsylvania

  • Ilya M Nemenman

    Emory University, Physics, Emory, Physics, Emory University

  View abstract →

• Different noise assumptions yield qualitatively different landscapes and transition paths in gene regulation models

  ORAL

  March 4, 2020, 5:30 PM – March 4, 2020, 5:42 PM

  Presenters

  • John Vastola

    Vanderbilt Univ

  Authors

  • John Vastola

    Vanderbilt Univ

  • William R. Holmes

    Vanderbilt Univ

  View abstract →

• Stochastic Modelling of Dynein Motors on a One-Dimensional Lattice: Dynamics and Stationary State

  ORAL

  March 4, 2020, 5:42 PM – March 4, 2020, 5:54 PM

  Presenters

  • Riya Nandi

    Department of Physics & Center for Soft Matter and Biological Physics, Virginia Tech

  Authors

  • Riya Nandi

    Department of Physics & Center for Soft Matter and Biological Physics, Virginia Tech

  • Priyanka .

    Department of Physics & Center for Soft Matter and Biological Physics, Virginia Tech, Virginia Tech

  View abstract →

• Limits to biochemical signalling in a changing environment as an inference problem

  ORAL

  March 4, 2020, 5:54 PM – March 4, 2020, 6:06 PM

  Presenters

  • Thierry Mora

    Ecole Normale Superieure

  Authors

  • Thierry Mora

    Ecole Normale Superieure

  • Ilya M Nemenman

    Emory University, Physics, Emory, Physics, Emory University

  View abstract →

• Human information processing in complex networks

  ORAL

  March 4, 2020, 6:06 PM – March 4, 2020, 6:18 PM

  Presenters

  • Christopher Lynn

    University of Pennsylvania

  Authors

  • Christopher Lynn

    University of Pennsylvania

  • Evangelia Papadopoulos

    University of Pennsylvania

  • Ari Kahn

    University of Pennsylvania

  • Danielle Bassett

    University of Pennsylvania

  View abstract →

• Information tradeoffs in sensing and sampling

  ORAL

  March 4, 2020, 6:18 PM – March 4, 2020, 6:30 PM

  Presenters

  • Caroline Holmes

    Princeton University

  Authors

  • Caroline Holmes

    Princeton University

  • William S Bialek

    princeton university, Department of Physics, Princeton University, Princeton University, Physics, Princeton University

  View abstract →

• Optical reservoir computing with tumor spheroids

  ORAL

  March 4, 2020, 6:30 PM – March 4, 2020, 6:42 PM

  Presenters

  • Claudio Conti

    Physics Department, Sapienza University of Rome, Univ of Rome La Sapienza

  Authors

  • Davide Pierangeli

    Physics Department, Sapienza University of Rome, Univ of Rome La Sapienza

  • Valentina Palmieri

    University Cattolica

  • Giulia Marcucci

    Physics Department, Sapienza University of Rome, Univ of Rome La Sapienza

  • Chiara Moriconi

    University Cattolica

  • Giordano Perini

    University Cattolica

  • Marco De Spirito

    University Cattolica

  • Massimiliano Papi

    University Cattolica

  • Claudio Conti

    Physics Department, Sapienza University of Rome, Univ of Rome La Sapienza

  View abstract →

• Stochastic Force Inference

  ORAL

  March 4, 2020, 6:42 PM – March 4, 2020, 6:54 PM

  Presenters

  • Pierre Ronceray

    Princeton University

  Authors

  • Pierre Ronceray

    Princeton University

  • Anna Frishman

    Technion

  View abstract →

• Predicting the future from the past in visual object motion: optimal representations of mixed stochastic/deterministic trajectories

  ORAL

  March 4, 2020, 6:54 PM – March 4, 2020, 7:06 PM

  Presenters

  • Vedant Sachdeva

    University of Chicago

  Authors

  • Vedant Sachdeva

    University of Chicago

  • Aleksandra Maria Walczak

    Ecole Normale Superieure

  • Thierry Mora

    Ecole Normale Superieure

  • Stephanie Palmer

    University of Chicago

  View abstract →

• Quantifying success and failure in simple models of large neural populations

  ORAL

  March 4, 2020, 7:06 PM – March 4, 2020, 7:18 PM

  Presenters

  • Leenoy Meshulam

    Massachusetts Institute of Technology MIT

  Authors

  • Leenoy Meshulam

    Massachusetts Institute of Technology MIT

  • Jeffrey Gauthier

    Swarthmore College

  • Carlos Brody

    Princeton Neuroscience Institute, Princeton University, Princeton University

  • David Tank

    Princeton Neuroscience Institute, Princeton University, Princeton University

  • William S Bialek

    princeton university, Department of Physics, Princeton University, Princeton University, Physics, Princeton University

  View abstract →

• Quantifying temporal information accumulation for biochemical signaling dynamics

  ORAL

  March 4, 2020, 7:18 PM – March 4, 2020, 7:30 PM

  Presenters

  • Ying Tang

    Institute for Quantitative and Computational Biosciences, University of California, Los Angeles

  Authors

  • Ying Tang

    Institute for Quantitative and Computational Biosciences, University of California, Los Angeles

  • Adewunmi Adelaja

    Institute for Quantitative and Computational Biosciences, University of California, Los Angeles

  • Xiaofeng Ye

    Department of Applied Mathematics & Statistics, Johns Hopkins University

  • Eric Deeds

    Institute for Quantitative and Computational Biosciences, University of California, Los Angeles

  • Roy Wollman

    Institute for Quantitative and Computational Biosciences, University of California, Los Angeles

  • Alexander Hoffmann

    Institute for Quantitative and Computational Biosciences, University of California, Los Angeles

  View abstract →