1 citations · 2 across the 11 of their papers we have counts for
5 papers · 1 filter
Towards Learning Representations of Policies in Two-Player Zero-Sum Imperfect-Information Games
Kevin Wang, Kevin Yang, Arjun Prakash +1
We investigate the problem of learning useful policy representations (embeddings) in two-player zero-sum imperfect-information games. We make three contributions: First, we introdu…
Chronax: A Jax Library for Forecasting and Conformal Inference
Xan Carey, Arsh Singh, Yash Deshmukh +8
Time-series forecasting is central to many scientific and industrial domains, such as energy systems, climate modeling, finance, and retail. While forecasting methods have evolved…
TempusBench: An Evaluation Framework for Time-Series Forecasting
Denizalp Goktas, Gerardo Riaño-Briceño, Omkar Tekawade +14
Foundation models have transformed natural language processing and computer vision, and a rapidly growing literature on time-series foundation models (TSFMs) seeks to replicate thi…
Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning
Arjun Prakash, Naicheng He, Kaicheng Guo +5
We investigate why deep neural networks suffer from loss of plasticity in continual learning, and thus fail to learn new tasks without reinitializing parameters. We show that this…
Bi-Level Policy Optimization with Nyström Hypergradients
Arjun Prakash, Naicheng He, Denizalp Goktas +2
The dependency of the actor on the critic in actor-critic (AC) reinforcement learning means that AC can be characterized as a bilevel optimization (BLO) problem, also called a Stac…