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  • ARNI Biological Learning Working Group

    1) Charlotte onboarded vision and audio MNIST dataloaders. She's focusing on predictive coding for sequential tasks (e.g., audio data/moving MNIST). 2) Todd built a multi-modal predictive coding baselines showing that…

  • 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…

  • 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…

  • 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…

  • 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…

  • 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