research
∙
02/16/2023
Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits
Probabilistic Circuits (PCs) are a general and unified computational fra...
share
research
∙
02/03/2023
Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents
In this paper, we study the problem of planning in Minecraft, a popular,...
research
∙
01/21/2023
Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction
We study the problem of learning goal-conditioned policies in Minecraft,...
research
∙
11/22/2022
Sparse Probabilistic Circuits via Pruning and Growing
Probabilistic circuits (PCs) are a tractable representation of probabili...
research
∙
11/20/2022
Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation
Learning new task-specific skills from a few trials is a fundamental cha...
research
∙
10/10/2022
Scaling Up Probabilistic Circuits by Latent Variable Distillation
Probabilistic Circuits (PCs) are a unified framework for tractable proba...
research
∙
11/23/2021
Lossless Compression with Probabilistic Circuits
Despite extensive progress on image generation, deep generative models a...
research
∙
06/04/2021
Tractable Regularization of Probabilistic Circuits
Probabilistic Circuits (PCs) are a promising avenue for probabilistic mo...
research
∙
02/11/2021
A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries
Circuit representations are becoming the lingua franca to express and re...
research
∙
06/15/2020
On Effective Parallelization of Monte Carlo Tree Search
Despite its groundbreaking success in Go and computer games, Monte Carlo...
research
∙
02/25/2020