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05/24/2023
Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners
The emergent few-shot reasoning capabilities of Large Language Models (L...
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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...
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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,...
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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,...
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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...
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10/24/2022
RulE: Neural-Symbolic Knowledge Graph Reasoning with Rule Embedding
Knowledge graph (KG) reasoning is an important problem for knowledge gra...
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10/14/2022
SQA3D: Situated Question Answering in 3D Scenes
We propose a new task to benchmark scene understanding of embodied agent...
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07/16/2021
Towards an Interpretable Latent Space in Structured Models for Video Prediction
We focus on the task of future frame prediction in video governed by und...
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06/29/2020
Handling Missing Data in Decision Trees: A Probabilistic Approach
Decision trees are a popular family of models due to their attractive pr...
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06/15/2020
On Effective Parallelization of Monte Carlo Tree Search
Despite its groundbreaking success in Go and computer games, Monte Carlo...
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02/25/2020
Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration
Off-policy reinforcement learning (RL) is concerned with learning a rewa...
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12/06/2019
LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning
We describe a policy learning approach to map visual inputs to driving c...
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10/05/2019
On Tractable Computation of Expected Predictions
Computing expected predictions has many interesting applications in area...
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03/05/2019
What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features
While discriminative classifiers often yield strong predictive performan...
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02/27/2019
Learning Logistic Circuits
This paper proposes a new classification model called logistic circuits....
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11/01/2018
Horizon: Facebook's Open Source Applied Reinforcement Learning Platform
In this paper we present Horizon, Facebook's open source applied reinfor...
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06/01/2018
Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing
Incentive mechanisms for crowdsourcing are designed to incentivize finan...
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11/29/2017
