1 citations · 1 across the 4 of their papers we have counts for
5 papers
Primal-Dual Flow Matching for Sample-Wise Constrained Generation
Zhengyan Huan, Peter Y. Lu, Shuchin Aeron
We consider the problem of learning to generate data while satisfying a prescribed \emph{sample-wise} constraint with a user-specified probability of constraint satisfaction. Start…
Inverse Problems Conditioned on Observation Ensembles: Applications and Methods
Zhengyan Huan, Camila Pazos, Martin Klassen +3
We introduce a new multivariate statistical problem that we refer to as the Ensemble-conditioned Inverse Problem (EIP). The aim of EIP is to invert for an ensemble that is distribu…
Constraint-Aware Flow Matching via Randomized Exploration
Zhengyan Huan, Jacob Boerma, Li-Ping Liu +1
We consider the problem of designing constraint-aware flow matching (FM) models that address the issue of constraint violations commonly observed in vanilla generative models. We c…
Towards Universal Unfolding of Detector Effects in High-Energy Physics using Denoising Diffusion Probabilistic Models
Camila Pazos, Shuchin Aeron, Pierre-Hugues Beauchemin +4
Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional u…
Resilient Constrained Reinforcement Learning
Dongsheng Ding, Zhengyan Huan, Alejandro Ribeiro
We study a class of constrained reinforcement learning (RL) problems in which multiple constraint specifications are not identified before training. It is challenging to identify a…