Calendar of Events
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CTN: Sebastian Seung
CTN: Sebastian Seung
Title: Insights into vision from interpreting a neuronal wiring diagram Host: Marcus Triplett Abstract: In 2023, the FlyWire Consortium released the neuronal wiring diagram of an adult fly brain. This contains as a corollary the first complete wiring diagram of a visual system, which has been used to identify all 200+ cell types that are intrinsic to the…
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CTN: Stephanie Palmer
CTN: Stephanie Palmer
Title: How behavioral and evolutionary constraints sculpt early visual processing Abstract: Biological systems must selectively encode partial information about the environment, as dictated by the capacity constraints at work in all living organisms. For example, we cannot see every feature of the light field that reaches our eyes; temporal resolution is limited by transmission noise and delays,…
Continual Learning Working Group: Kick Off
Continual Learning Working Group: Kick Off
Speaker: Mengye Ren Title: Lifelong and Human-like Learning in Foundation Models Abstract: Real-world agents, including humans, learn from online, lifelong experiences. However, today’s foundation models primarily acquire knowledge through offline, iid learning, while relying on in-context learning for most online adaptation. It is crucial to equip foundation models with lifelong and human-like learning abilities to enable more flexible…
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ARNI NSF Site Visit
ARNI NSF Site Visit
NSF Site Visit - The NSF team will evaluate the progress and achievements of ARNI’s projects to date and provide recommendations to steer future directions and funding for the project. If you are interested in learning more about ARNI over-all, join this Zoom link from 9am to 12pm or 2pm to 4:30pm.
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CTN: Eva Dyer
CTN: Eva Dyer
Title: Large-scale pretraining on neural data allows for transfer across individuals, tasks and species Abstract: As neuroscience datasets grow in size and complexity, integrating diverse data sources to achieve a comprehensive understanding of brain function presents both an opportunity and a challenge. In this talk, I will introduce our approach to developing a multi-source foundation model for…
Continual Learning Working Group: Haozhe Shan
Continual Learning Working Group: Haozhe Shan
Speaker: Haozhe Shan Title: A theory of continual learning in deep neural networks: task relations, network architecture and learning procedure Abstract: Imagine listening to this talk and afterwards forgetting everything else you’ve ever learned. This absurd scenario would be commonplace if the brain could not perform continual learning (CL) – acquiring new skills and knowledge without…
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Multi-resource-cost Optimization for Neural Networks Models Working Group (NNMS): Tom Griffiths
Multi-resource-cost Optimization for Neural Networks Models Working Group (NNMS): Tom Griffiths
Title: Bounded optimality: A cognitive perspective on neural computation with resource limitations
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Multi-resource-cost Optimization for Neural Networks Models Working Group (NNMS): Simon Laughlin
Multi-resource-cost Optimization for Neural Networks Models Working Group (NNMS): Simon Laughlin
Title: Neuronal energy consumption: basic measures and trade-offs, and their effects on efficiency Zoom: https://columbiauniversity.zoom.us/j/98299154214?pwd=1J3J0lEpF6XdqHkHy02c7LuD6xUWx2.1
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Continual Learning Working Group: Amogh Inamdar
Continual Learning Working Group: Amogh Inamdar
Title: Taskonomy: Disentangling Task Transfer Learning Abstract: TBD Link: http://taskonomy.stanford.edu/taskonomy_CVPR2018.pdf