4 papers
Evaluating GFlowNet from partial episodes for stable and flexible policy-based training
Puhua Niu, Shili Wu, Xiaoning Qian
Generative Flow Networks (GFlowNets) were developed to learn policies for efficiently sampling combinatorial candidates by interpreting their generative processes as trajectories i…
Robust Behavior Cloning Via Global Lipschitz Regularization
Shili Wu, Yizhao Jin, Puhua Niu +2
Behavior Cloning (BC) is an effective imitation learning technique and has even been adopted in some safety-critical domains such as autonomous vehicles. BC trains a policy to mimi…
GFlowNet Training by Policy Gradients
Puhua Niu, Shili Wu, Mingzhou Fan +1
Generative Flow Networks (GFlowNets) have been shown effective to generate combinatorial objects with desired properties. We here propose a new GFlowNet training framework, with po…
Epidemiological Model Calibration via Graybox Bayesian Optimization
Puhua Niu, Byung-Jun Yoon, Xiaoning Qian
In this study, we focus on developing efficient calibration methods via Bayesian decision-making for the family of compartmental epidemiological models. The existing calibration me…