research
∙
03/13/2023
Kernel Density Bayesian Inverse Reinforcement Learning
Inverse reinforcement learning (IRL) is a powerful framework to infer an...
share
research
∙
10/15/2021
Multi-group Gaussian Processes
Gaussian processes (GPs) are pervasive in functional data analysis, mach...
research
∙
10/06/2021
Nested Policy Reinforcement Learning
Off-policy reinforcement learning (RL) has proven to be a powerful frame...
research
∙
06/02/2021
Spectral embedding for dynamic networks with stability guarantees
We consider the problem of embedding a dynamic network, to obtain time-e...
research
∙
03/22/2021
Neural Lumigraph Rendering
Novel view synthesis is a challenging and ill-posed inverse rendering pr...
research
∙
02/12/2021
Contrastive latent variable modeling with application to case-control sequencing experiments
High-throughput RNA-sequencing (RNA-seq) technologies are powerful tools...
research
∙
12/14/2020
Probabilistic Contrastive Principal Component Analysis
Dimension reduction is useful for exploratory data analysis. In many app...
research
∙
07/20/2020