104 citations · 374 across the 40 of their papers we have counts for
6 papers · 1 filter
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…