CTN: Naureen Ghani
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: Mice wiggle a wheel to boost the salience of low visual contrast stimuli Abstract: From the Welsh tidy mouse to the New York City pizza rat, movement belies rodent intelligence. We show that head-fixed…
CTN: Jacob Macke
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: Building mechanistic models of neural computations with simulation-based machine learning Abstract: Experimental techniques now make it possible to measure the structure and function of neural circuits at an unprecedented scale and…
ARNI Seminar Series Kick Off: Speaker Jim DiCarlo
Zuckerman Institute - L7-119 3227 Broadway, New York, NY, United StatesTitle: Do contemporary, machine-executable models (aka digital twins) of the primate ventral visual system unlock the ability to non-invasively, beneficially modulate high level brain states? Abstract: In this talk, I…
Continual Learning Working Group: Brainstorming
CEPSR 620 Schapiro 530 W. 120th StZoom Link: https://columbiauniversity.zoom.us/j/97176853843?pwd=VLZdh6yqHBcOQhdf816lkN5ByIpIsF.1
CTN: Tanya Sharpee
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesSeminar 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
Continual Learning Working Group: Nikita Rajaneesh
CEPSR 6LW4 Computer Science Department 500 West 120 StreetTitle: 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…
CTN: Catherine Hartley
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: TBD Abstract: TBD
CTN: Seminar Speaker Alessandro Ingrosso
Zuckerman Institute - L3-079 3227 Broadway, New York, NY, United StatesTitle: 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…
Continual Learning Working Group: Lea Duncker
CEPSR 620 Schapiro 530 W. 120th StTitle: TBD Abstract TBD: Zoom Link: https://columbiauniversity.zoom.us/j/97176853843?pwd=VLZdh6yqHBcOQhdf816lkN5ByIpIsF.1