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…
CTN Seminar: Andrew Leifer
Zuckerman Institute - L5-084 3227 Broadway, New York, NY, United StatesTitle: TBD Abstract: TBD
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…
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…