194 citations · 246 across the 14 of their papers we have counts for
26 papers
Gaussian-Bernoulli RBMs Without Tears
Renjie Liao, Simon Kornblith, Mengye Ren +2
We revisit the challenging problem of training Gaussian-Bernoulli restricted Boltzmann machines (GRBMs), introducing two innovations. We propose a novel Gibbs-Langevin sampling alg…
Learning to Reason With Relational Abstractions
Andrew J. Nam, Mengye Ren, Chelsea Finn +1
Large language models have recently shown promising progress in mathematical reasoning when fine-tuned with human-generated sequences walking through a sequence of solution steps.…
Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes
Sean Segal, Nishanth Kumar, Sergio Casas +4
Self-driving vehicles must perceive and predict the future positions of nearby actors in order to avoid collisions and drive safely. A learned deep learning module is often respons…
Cost-Efficient Online Hyperparameter Optimization
Jingkang Wang, Mengye Ren, Ilija Bogunovic +2
Recent work on hyperparameters optimization (HPO) has shown the possibility of training certain hyperparameters together with regular parameters. However, these online HPO algorith…
SceneGen: Learning to Generate Realistic Traffic Scenes
Shuhan Tan, Kelvin Wong, Shenlong Wang +3
We consider the problem of generating realistic traffic scenes automatically. Existing methods typically insert actors into the scene according to a set of hand-crafted heuristics…
Adversarial Attacks On Multi-Agent Communication
James Tu, Tsunhsuan Wang, Jingkang Wang +3
Growing at a fast pace, modern autonomous systems will soon be deployed at scale, opening up the possibility for cooperative multi-agent systems. Sharing information and distributi…