The Science of Deep Learning

Creativity and Collaboration: Revisiting Cybernetic Serendipity Colloquium Agenda

 

//// Role/Play: Collaborative Creativity and Creative Collaborations Student Fellows Symposium Agenda

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  • Wednesday, March 13, 2019
  •  

    Lecture

    9:00 AM  -  9:15 AM
    Opening Remarks: Marcia McNutt
    NAS Building 2101 Constitution Ave NW
    Session I: The State of Deep Learning: Opening Remarks: Marcia McNutt, President National Academy of Sciences
    9:15 AM  -  9:20 AM
    Special Issue Announcement, David Donoho
    NAS Building 2101 Constitution Ave NW
    Session I: The State of Deep Learning: Special Issue Announcement, David Donoho, Stanford University
    Speakers:
    9:20 AM  -  10:00 AM
    Session I: The State of Deep Learning: Overview Talk (I) Amnon Shashua
    NAS Building 2101 Constitution Ave NW
    Session I: The State of Deep Learning: Successes and Challenges in Modern Artificial Intelligence , Amnon Shashua, Hebrew University / Mobileye
    Speakers:
    10:00 AM  -  10:40 AM
    Session I: The State of Deep Learning: Overview talk (II) Jitendra Malik
    NAS Building 2101 Constitution Ave NW
    Session I: The State of Deep Learning: Overview talk (II) Jitendra Malik, University of California, Berkeley
    Speakers:
     

    Break

    10:40 AM  -  11:00 AM
    Break
    NAS Building 2101 Constitution Ave NW
    Break
     

    Lecture

    11:00 AM  -  11:30 AM
    Session I: The State of Deep Learning: Talk: Chris Manning
    NAS Building 2101 Constitution Ave NW
    Session I: The State of Deep Learning: Talk: Chris Manning, Stanford University
    Speakers:
    11:30 AM  -  12:00 PM
    Talk: Oriol Vinyals
    NAS Building 2101 Constitution Ave NW
    Session I: The State of Deep Learning: Talk: Oriol Vinyals, Google AI
    Speakers:
    12:00 PM  -  12:30 PM
    Critical Perspective: Strengths and Fallacies in the Dominant DL Narrative
    NAS Building 2101 Constitution Ave NW
    Session I: The State of Deep Learning
    (Panel) Critical Perspective: Strengths and Fallacies in the Dominant DL Narrative
    Terrence Sejnowski, Salk Institute for Biological Studies
    Tomaso Poggio, Massachusetts Institute of Technology
    Regina Barzilay, Massachusetts Institute of Technology
    Rodney Brooks, Massachusetts Institute of Technology
     

    Dining

    12:30 PM  -  1:30 PM
    Lunch
    NAS Building 2101 Constitution Ave NW
    Lunch
     

    Lecture

    1:30 PM  -  2:00 PM
    Session II: Deep Learning in Science: Talk: Regina Barzilay
    NAS Building 2101 Constitution Ave NW
    Session II: Deep Learning in Science: Talk: Regina Barzilay, Massachusetts Institute of Technology
    Speakers:
    2:00 PM  -  2:30 PM
    Session II: Deep Learning in Science: Talk: Kyle Cranmer
    NAS Building 2101 Constitution Ave NW
    Session II: Deep Learning in Science: Talk: Kyle Cranmer, New York University
    Speakers:
    2:30 PM  -  3:00 PM
    Session II: Deep Learning in Science: Talk: Olga Troyanskaya
    NAS Building 2101 Constitution Ave NW
    Session II: Deep Learning in Science: Talk: Olga Troyanskaya, Princeton University
    Speakers:
     

    Break

    3:00 PM  -  3:30 PM
    Break
    NAS Building 2101 Constitution Ave NW
    Break
     

    Lecture

    3:30 PM  -  4:00 PM
    Session II: Deep Learning in Science: Talk: Eero Simoncelli
    NAS Building 2101 Constitution Ave NW
    Session II: Deep Learning in Science: Talk: Eero Simoncelli, New York University
    Speakers:
    4:00 PM  -  4:15 PM
    Counterpoint: Bruno Olshausen
    NAS Building 2101 Constitution Ave NW
    Session II: Deep Learning in Science: Counterpoint: Bruno Olshausen, University of California, Berkeley
    Speakers:
    4:15 PM  -  4:30 PM
    Counterpoint: Antonio Torralba
    NAS Building 2101 Constitution Ave NW
    Session II: Deep Learning in Science: Counterpoint: Antonio Torralba, Massachusetts Institute of Technology
    Speakers:
    4:30 PM  -  5:00 PM
    Critical Perspective: Scientific Funding for DL Development: Justified? Efficient?
    NAS Building 2101 Constitution Ave NW

    Session II: Deep Learning in Science
    (Panel) Critical Perspective: Scientific Funding for DL Development: Justified? Efficient?
    Ronald Coifman, Yale University
    Konrad Kording, University of Pennsylvania
    Doina Precup, McGill University
    Chris Manning, Stanford University

     

    Dining

    5:00 PM  -  6:00 PM
    Reception
    NAS Building 2101 Constitution Ave NW
    Reception
     

    Lecture

    6:00 PM  -  8:00 PM
    Annual Sackler Lecture
    NAS Building 2101 Constitution Ave NW
    Annual Sackler Lecture: Introduction by Marcia McNutt, President, National Academy of Sciences Rodney Brooks, Massachusetts Institute of Technology
    Speakers:
  • Thursday, March 14, 2019
  •  

    Workshop

    8:00 AM  -  8:45 AM
    Breakout Session: Legal and security implications
    NAS Building 2101 Constitution Ave NW
    Interpretability of DL systems: legal and security implications
     Optional 
    8:00 AM  -  8:45 AM
    Breakout Session: Academia and Industry research
    NAS Building 2101 Constitution Ave NW
    DL research in academia and in industry: what are the differences?, Moderator - Ronald Coifman, Yale University
    Moderator:
     Optional 
    8:00 AM  -  8:45 AM
    Breakout Session: Funding
    NAS Building 2101 Constitution Ave NW
    Science funding and deep learning research. Rencontres between researchers and the Washington science funding community. (Under development)
     Optional 
    8:00 AM  -  8:45 AM
    Breakout Session: Validation and stability
    NAS Building 2101 Constitution Ave NW
    Validation and stability of DL systems, Moderator - Anders Hansen, Cambridge University
    Moderator:
     Optional 
     

    Break

    8:45 AM  -  9:00 AM
    Break
    NAS Building 2101 Constitution Ave NW
    Break
     

    Lecture

    9:00 AM  -  9:30 AM
    Session III: Theoretical Perspectives on Deep Learning: Talk: Tomaso Poggio
    NAS Building 2101 Constitution Ave NW
    Session III: Theoretical Perspectives on Deep Learning:
    Networks of neurons for learning and representing symbols in the brain, Tomaso Poggio, Massachusetts Institute of Technology
    Speakers:
    9:30 AM  -  10:00 AM
    Session III: Theoretical Perspectives on Deep Learning: Talk: Nati Srebro
    NAS Building 2101 Constitution Ave NW
    Session III: Theoretical Perspectives on Deep Learning: Talk: Nati Srebro, Toyota Technological Institute at Chicago
    10:00 AM  -  10:30 AM
    Session III: Theoretical Perspectives on Deep Learning: Talk: Peter Bartlett
    NAS Building 2101 Constitution Ave NW
    Session III: Theoretical Perspectives on Deep Learning: Talk: Peter Bartlett, University of California, Berkeley
    Speakers:
     

    Break

    10:30 AM  -  10:45 AM
    Break
    NAS Building 2101 Constitution Ave NW
    Break
     

    Lecture

    10:45 AM  -  11:00 AM
    Session III: Theoretical Perspectives on Deep Learning: Counterpoint: Konrad Kording
    NAS Building 2101 Constitution Ave NW
    Session III: Theoretical Perspectives on Deep Learning: Counterpoint: Konrad Kording, University of Pennsylvania
    Speakers:
    11:00 AM  -  11:15 AM
    Counterpoint: Anders Hansen
    NAS Building 2101 Constitution Ave NW
    Session III: Theoretical Perspectives on Deep Learning: Counterpoint: Anders Hansen, Cambridge University
    Speakers:
    11:15 AM  -  11:30 AM
    Counterpoint: Ronald Coifman
    NAS Building 2101 Constitution Ave NW
    Session III: Theoretical Perspectives on Deep Learning: Counterpoint: Ronald Coifman, Yale University
    Speakers:
    11:30 AM  -  12:00 PM
    Critical Perspective: Could a good DL theory change practice?
    NAS Building 2101 Constitution Ave NW
    Session III: Theoretical Perspectives on Deep Learning
    (Panel) Critical Perspective:Could a good DL theory change practice? 
    Eero Simoncelli, New York University
    Jon Kleinberg, Cornell University
    Haim Sompolinsky, Hebrew University of Jerusalem
    Julia Kempe, New York University Center for Data Science
     

    Dining

    12:00 PM  -  1:00 PM
    Lunch and Poster Session
    NAS Building 2101 Constitution Ave NW
    Poster will be presented by Young Researchers during lunch.
     

    Lecture

    1:00 PM  -  1:15 PM
    Session IV: Experimental Perspectives on Deep Learning: Short talk: Jonathon Phillips
    NAS Building 2101 Constitution Ave NW
    Session IV: Experimental Perspectives on Deep Learning: Short talk: Jonathon Phillips, National Institute of Standards and Technology
    Speakers:
    1:15 PM  -  1:30 PM
    Session IV: Experimental Perspectives on Deep Learning: Short talk: Isabelle Guyon
    NAS Building 2101 Constitution Ave NW
    Session IV: Experimental Perspectives on Deep Learning: Short talk: Isabelle Guyon, Paris-Sud University & ClopiNet
    Speakers:
    1:30 PM  -  2:00 PM
    Session IV: Experimental Perspectives on Deep Learning: Talk: Doina Precup
    NAS Building 2101 Constitution Ave NW
    Session IV: Experimental Perspectives on Deep Learning: Talk: Doina Precup, McGill University
    Speakers:
    2:00 PM  -  2:30 PM
    Session IV: Experimental Perspectives on Deep Learning: Talk: Haim Sampolinsky
    NAS Building 2101 Constitution Ave NW
    Session IV: Experimental Perspectives on Deep Learning: Talk: Haim Sampolinsky, Hebrew University of Jerusalem
    Speakers:
     

    Break

    2:30 PM  -  2:45 PM
    Break
    NAS Building 2101 Constitution Ave NW
    Break
     

    Lecture

    2:45 PM  -  3:00 PM
    Counterpoint: Moritz Hardt
    NAS Building 2101 Constitution Ave NW
    Session IV: Experimental Perspectives on Deep Learning: Counterpoint: Moritz Hardt, University of California, Berkeley
    Speakers:
    3:00 PM  -  3:15 PM
    Counterpoint: Tara Sainath
    NAS Building 2101 Constitution Ave NW
    Session IV: Experimental Perspectives on Deep Learning: Counterpoint: Tara Sainath, Google AI
    Speakers:
    3:15 PM  -  3:45 PM
    Critical Perspective Panel: What’s missing in today’s experimental analysis of DL?
    NAS Building 2101 Constitution Ave NW
    Session IV: Experimental Perspectives on Deep Learning
    (Panel) Critical Perspective: What’s missing in today’s experimental analysis of DL?
    Jitendra Malik, University of California, Berkeley
    Peter Bartlett, University of California, Berkeley
    Antonio Torralba, Massachusetts Institute of Technology
     

    Break

    3:45 PM  -  4:00 PM
    Break
    NAS Building 2101 Constitution Ave NW
    Break
     

    Lecture

    4:00 PM  -  4:15 PM
    Summary: Right ways forward?: Terrence Sejnowski
    NAS Building 2101 Constitution Ave NW
    Summary: Right ways forward?: Terrence Sejnowski, Salk Institute for Biological Studies
    4:15 PM  -  4:30 PM
    Summary: Right ways forward?: Leon Bottou
    NAS Building 2101 Constitution Ave NW
    Summary: Right ways forward?: Leon Bottou, FaceBook AI Research
    Speakers:
    4:30 PM  -  4:45 PM
    Summary: Right ways forward?: Jon Kleinberg
    NAS Building 2101 Constitution Ave NW
    Summary: Right ways forward?: Jon Kleinberg, Cornell University
    Speakers:
    4:45 PM  -  5:00 PM
    Summary: Right ways forward?: Ali Rahimi
    NAS Building 2101 Constitution Ave NW
    Summary: Right ways forward?: Ali Rahimi, Google, Inc.
    Speakers:
     

    Adjourn

    5:00 PM  -  5:01 PM
    Adjourn
    NAS Building 2101 Constitution Ave NW
    Adjourn
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