104 citations · 374 across the 40 of their papers we have counts for
42 papers
Budgeting Counterfactual for Offline RL
Yao Liu, Pratik Chaudhari, Rasool Fakoor
The main challenge of offline reinforcement learning, where data is limited, arises from a sequence of counterfactual reasoning dilemmas within the realm of potential actions: What…
Taming AI Bots: Controllability of Neural States in Large Language Models
Stefano Soatto, Paulo Tabuada, Pratik Chaudhari +1
We tackle the question of whether an agent can, by suitable choice of prompts, control an AI bot to any state. To that end, we first introduce a formal definition of ``meaning'' th…
Learning Capacity: A Measure of the Effective Dimensionality of a Model
Daiwei Chen, Wei-Kai Chang, Pratik Chaudhari
We use a formal correspondence between thermodynamics and inference, where the number of samples can be thought of as the inverse temperature, to study a quantity called ``learning…
The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold
Jialin Mao, Itay Griniasty, Han Kheng Teoh +5
We develop information-geometric techniques to analyze the trajectories of the predictions of deep networks during training. By examining the underlying high-dimensional probabilis…
Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis
Yansong Gao, Zhihong Pan, Xin Zhou +2
Denoising diffusion probabilistic models (DDPMs) are a class of powerful generative models. The past few years have witnessed the great success of DDPMs in generating high-fidelity…
Mesh Strikes Back: Fast and Efficient Human Reconstruction from RGB videos
Rohit Jena, Pratik Chaudhari, James Gee +3
Human reconstruction and synthesis from monocular RGB videos is a challenging problem due to clothing, occlusion, texture discontinuities and sharpness, and framespecific pose chan…