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Continual Learning Working Group: Lea Duncker
CEPSR 620 Schapiro 530 W. 120th StTitle: 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…
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CTN Lab: Ashok Litwin-Kumar
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: 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…
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CTN: Mazviita Chirimuuta
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: 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…
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CTN: Mehdi Azabou, ARNI Postdoctorate Research Scientist
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: 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…
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CTN: Adam Cohen
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: 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…
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CTN: Jonathan Pillow
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: 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…
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CTN: Monday Lab Kim Stachenfeld
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: 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.…
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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…
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CTN: Hidenori Tanaka
Zuckerman Institute- Kavli Auditorium 9th Fl 3227 Broadway, NYHidenori Tanaka Title and Abstract: TBD
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CTN: Eva Naumann
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle and Abstract: TBD
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CTN Monda Lab: Liam Paninski
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle and Abstract: TBD
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ARNI Continual Learning Working Group Spring Opening Meeting
CEPSR 620 Schapiro 530 W. 120th StFrom: Tom Zollo In Y2, the aim is to use this working group as a launchpad for a larger ARNI continual learning project (which we hope to spawn multiple subprojects and papers). We hope for this group to tackle issues that are relevant to both modern practitioners and the ARNI mission of connecting artificial and natural intelligence.…
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