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  • CTN: SueYeon Chung

    Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United States

    SueYeon Chung Title: Computing with Neural Manifolds: A Multi-Scale Framework for Understanding Biological and Artificial Neural Networks Abstract: Recent breakthroughs in experimental neuroscience and machine learning have opened new frontiers in understanding the computational principles governing neural circuits and artificial neural networks (ANNs). Both biological and artificial systems exhibit an astonishing degree of orchestrated information…

  • ARNI Continual Learning Working Group Meeting

    CEPSR 620 Schapiro 530 W. 120th St

    We are aiming to accelerate progress on the benchmark, and will demo a working prototype very soon. If you are interested in contributing to our project, we strongly encourage you to participate so that we can fix and implement our plan of action for the coming few months.

  • CTN: Mitra Javadzadeh

    Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United States

    Title: Inter-area connectivity and the emergence of multi-timescale cortical dynamics Abstract: The brain generates behaviors spanning a wide range of timescales, from rapid sensory responses to the slow integrative processes underlying cognition. How does the anatomical connectivity of the neocortex give rise to such flexible, multi-timescale dynamics? In this talk, I will examine how the…

  • CTN: Denise Cai

    Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United States

    Denise Cai Title: Dynamic neural ensembles support memory stability and flexibility across the lifetime Abstract: Creating stable memories is critical for survival. An animal relies on past learning to navigate its environment, avoid dangerous situations, and find needed resources. Because the environment is dynamic, stable memories must be updated with new information to enable responses…

  • CTN: Andreas Tolias

    Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United States

    Title: Foundation models of the brain Abstract: You … your memories and ambitions, your sense of personal identity and free will, are in fact no more than the behavior of a vast…

  • CTN: Farzaneh Najafi

    Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United States
  • Speaker: Katherine Xu – Language and Vision Working Group

    Virtual

    Title: Are Vision-Language Models Checking or Looking? Abstract: Today’s AI vision systems are trained on vast amounts of data, yet it remains unclear whether they simply retrieve memorized answers or actively…