Zoom Link:  https://columbiauniversity.zoom.us/j/97176853843?pwd=VLZdh6yqHBcOQhdf816lkN5ByIpIsF.1

Seminar Time: 11:30am Date: 11/8/2024 Location: JLG, L5-084  Host: Krishan Kumar   Title: Building mechanistic models of neural computations with simulation-based machine learnin

Title: Wandering Within a World A discussion on Wandering Within a World: Online Contextualized Few-Shot Learning, this 2021 paper by our very own Rich Zemel leverages contextual information in a…

Title: TBD Abstract: TBD

Title: Statistical mechanics of transfer learning in the proportional limit Abstract: Transfer learning (TL) is a well-established machine learning technique to boost the generalization performance on a specific (target) task…

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…

Title: TBD Abstract: TBD

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…

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…

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…

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 robust and comprehensive computational models that generalize across diverse conditions, tasks, and individuals. Our work is motivated by the need for a large-scale foundation model…

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 their footprints, and what patterns of spiking and synaptic inputs can activate them?  We mapped bioelectrical signals throughout dendritic arbors of pyramidal cells in behaving…