Events
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CTN: Nao Uchida
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: A normative perspective on diversity of dopamine neurons Abstract: TBD
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Speaker: Xaq Pitkow ARNI WG Multi-resource-cost optimization of neural network models
Zuckerman Institute - L3-079 3227 Broadway, New York, NY, United StatesTitle: Frugal Inference for Control Abstract: A key challenge in advancing artificial intelligence is achieving the right balance between utility maximization and resource use by both external movement and internal computation. While…
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Continual Learning Working Group
CEPSR 620 Schapiro 530 W. 120th StTo kick off the Continual Learning Working Group activities for this year, the Continual Learning working group will meet on Thursday, Jan 22 at 3pm on Zoom and in CEPSR 620. The meeting will…
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CTN: Scott Linderman
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: When and How to Parallelize Seemingly Sequential Models Abstract: Transformers have become the de facto model for sequential data in large part because they are well adapted to modern hardware:…
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Language and Vision Working Group
Initial Meeting! About: The ARNI Language & Vision Working Group aims to bring together researchers across neuroscience, cognitive science, computer science, and AI to collaboratively advance our understanding of how…
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Speaker: Thuy Nguyen – ARNI Frontier Models for Neuroscience and Behavior Working Group
MILA A14Title:A multimodal sleep foundation model for disease prediction Abstract: Sleep is a fundamental biological process with broad implications for physical and mental health, yet its complex relationship with disease remains…
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CTN: Herbert Zheng Wu
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesHerbert Zheng Wu Title: Neural Basis of Leader–Follower Dynamics in Cooperative Behavior Abstract: Cooperation allows social species to achieve outcomes that individuals cannot accomplish alone. Even in simple groups, cooperative behavior often…
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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…
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CTN: SueYeon Chung
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesSueYeon 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…
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ARNI Continual Learning Working Group Meeting
CEPSR 620 Schapiro 530 W. 120th StWe 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…
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CTN: Mitra Javadzadeh
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: 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…
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ARNI Biological Learning Working Group
VirtualContinuation from prior meetings Zoom Link- Upon request @ [email protected]
