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  • Lecture in AI: Danqi Chen

    Davis Auditorium 530 W 120th St, New York, NY 10027, New York, NY

    Title: Training Language Models in Academic: Research Questions and Opportunities Abstract: Large language models have emerged as transformative tools in artificial intelligence, demonstrating unprecedented capabilities in understanding and generating human language. While these models have achieved remarkable performance across a wide range of benchmarks and enabled groundbreaking applications, their development has been predominantly concentrated within…

  • CTN Seminar: Andrew Leifer

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

    Title: TBD Abstract: TBD

  • Continual Learning Working Group: Lea Duncker

    CEPSR 620 Schapiro 530 W. 120th St

    Title: Task-dependent low-dimensional population dynamics for robustness and learning Abstract: Biological systems face dynamic environments that require flexibly deploying learned skills and continual learning of new tasks. It is not well understood how these systems balance the tension between flexibility for learning and robustness for memory of previous behaviors. Neural activity underlying single, highly controlled…

  • CTN Lab: Ashok Litwin-Kumar

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

    Title: Searching for symmetries in connectome data Abstract: I will talk about work with Haozhe Shan on identifying structure in connectome data that suggests a cell type encodes one or…

  • CTN: Mazviita Chirimuuta

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

    Title: Neuromorphic Computing and the Significance of Medium Dependence   Abstract: The increasingly prohibitive cost of energy demanded by large artificial neural networks (ANNs) is giving new impetus to research and…

  • CTN: Mehdi Azabou, ARNI Postdoctorate Research Scientist

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

    Title: Building foundation models for neuroscience Abstract: Current methodologies for recording brain activity often provide narrow views of the brain's function. This fragmentation of datasets has hampered the development of…

  • CTN: Adam Cohen

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

    Title: Mapping bioelectrical signals, from dendrites to circuits Abstract: Neuronal dendrites are excitable, but what are these excitations for?  Are dendritic excitations involved in integration?  Or in mediating back-propagation?  What are…

  • CTN: Jonathan Pillow

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

    Title: Disentangling the Roles of Distinct Cell Classes with Cell-Type Dynamical Systems   Abstract: Latent dynamical systems have been widely used to characterize the dynamics of neural population activity in the…

  • CTN: Monday Lab Kim Stachenfeld

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

    Title: Discovering Symbolic Cognitive Models from Human and Animal Behavior with CogFunSearch Abstract: A key goal of cognitive science is to discover mathematical models that describe how the brain implements cognitive processes.…

  • ARNI Biological Learning Working Group

    Title: Brain-like learning with exponentiated gradients and Learning to live with Dale’s principle: ANNs with separate excitatory and inhibitory units Meeting Summary: Our focus will be on answering the following…

  • CTN: Hidenori Tanaka

    Zuckerman Institute- Kavli Auditorium 9th Fl 3227 Broadway, NY

    Hidenori Tanaka Title and Abstract: TBD

  • CTN: Eva Naumann

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

    Title and Abstract: TBD