33 citations · 60 across the 5 of their papers we have counts for
6 papers · 1 filter
Parallel Sampling of Diffusion Models
Andy Shih, Suneel Belkhale, Stefano Ermon +2
Diffusion models are powerful generative models but suffer from slow sampling, often taking 1000 sequential denoising steps for one sample. As a result, considerable efforts have b…
Long Horizon Temperature Scaling
Andy Shih, Dorsa Sadigh, Stefano Ermon
Temperature scaling is a popular technique for tuning the sharpness of a model distribution. It is used extensively for sampling likely generations and calibrating model uncertaint…
Conditional Imitation Learning for Multi-Agent Games
Andy Shih, Stefano Ermon, Dorsa Sadigh
While advances in multi-agent learning have enabled the training of increasingly complex agents, most existing techniques produce a final policy that is not designed to adapt to a…
On the Critical Role of Conventions in Adaptive Human-AI Collaboration
Andy Shih, Arjun Sawhney, Jovana Kondic +2
Humans can quickly adapt to new partners in collaborative tasks (e.g. playing basketball), because they understand which fundamental skills of the task (e.g. how to dribble, how to…
Probabilistic Circuits for Variational Inference in Discrete Graphical Models
Andy Shih, Stefano Ermon
Inference in discrete graphical models with variational methods is difficult because of the inability to re-parameterize gradients of the Evidence Lower Bound (ELBO). Many sampling…
On Tractable Representations of Binary Neural Networks
Weijia Shi, Andy Shih, Adnan Darwiche +1
We consider the compilation of a binary neural network's decision function into tractable representations such as Ordered Binary Decision Diagrams (OBDDs) and Sentential Decision D…