no code implementations • 18 Apr 2024 • James Seale Smith, Lazar Valkov, Shaunak Halbe, Vyshnavi Gutta, Rogerio Feris, Zsolt Kira, Leonid Karlinsky
This continual learning (CL) phenomenon has been extensively studied, but primarily in a setting where only a small amount of past data can be stored.
no code implementations • 11 Jun 2023 • Lazar Valkov, Akash Srivastava, Swarat Chaudhuri, Charles Sutton
To address this challenge, we develop a modular CL framework, called PICLE, that accelerates search by using a probabilistic model to cheaply compute the fitness of each composition.
2 code implementations • NeurIPS 2018 • Lazar Valkov, Dipak Chaudhari, Akash Srivastava, Charles Sutton, Swarat Chaudhuri
We present a neurosymbolic framework for the lifelong learning of algorithmic tasks that mix perception and procedural reasoning.
1 code implementation • NeurIPS 2017 • Akash Srivastava, Lazar Valkov, Chris Russell, Michael U. Gutmann, Charles Sutton
Deep generative models provide powerful tools for distributions over complicated manifolds, such as those of natural images.