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09/20/2023
Hierarchical reinforcement learning with natural language subgoals
Hierarchical reinforcement learning has been a compelling approach for a...
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05/30/2023
NetHack is Hard to Hack
Neural policy learning methods have achieved remarkable results in vario...
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03/31/2023
Accelerating exploration and representation learning with offline pre-training
Sequential decision-making agents struggle with long horizon tasks, sinc...
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02/22/2023
Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC
Since their introduction, diffusion models have quickly become the preva...
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02/01/2023
Collaborating with language models for embodied reasoning
Reasoning in a complex and ambiguous environment is a key goal for Reinf...
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01/29/2023
Distilling Internet-Scale Vision-Language Models into Embodied Agents
Instruction-following agents must ground language into their observation...
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01/27/2023
EmbedDistill: A Geometric Knowledge Distillation for Information Retrieval
Large neural models (such as Transformers) achieve state-of-the-art perf...
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10/31/2022
Learning to Navigate Wikipedia by Taking Random Walks
A fundamental ability of an intelligent web-based agent is seeking out a...
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07/20/2021
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
We present DrQ-v2, a model-free reinforcement learning (RL) algorithm fo...
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07/08/2021
Imitation by Predicting Observations
Imitation learning enables agents to reuse and adapt the hard-won expert...
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03/14/2021
Offline Reinforcement Learning with Fisher Divergence Critic Regularization
Many modern approaches to offline Reinforcement Learning (RL) utilize be...
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02/22/2021
Reinforcement Learning with Prototypical Representations
Learning effective representations in image-based environments is crucia...
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02/20/2021
Decoupling Value and Policy for Generalization in Reinforcement Learning
Standard deep reinforcement learning algorithms use a shared representat...
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07/06/2020
Fast Adaptation via Policy-Dynamics Value Functions
Standard RL algorithms assume fixed environment dynamics and require a s...
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06/23/2020
Automatic Data Augmentation for Generalization in Deep Reinforcement Learning
Deep reinforcement learning (RL) agents often fail to generalize to unse...
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04/28/2020
Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
We propose a simple data augmentation technique that can be applied to s...
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04/27/2020
Energy-based models for atomic-resolution protein conformations
We propose an energy-based model (EBM) of protein conformations that ope...
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10/02/2019
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
Training an agent to solve control tasks directly from high-dimensional ...
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09/12/2019
Finding Generalizable Evidence by Learning to Convince Q A Models
We propose a system that finds the strongest supporting evidence for a g...
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01/17/2019
Disentangling Video with Independent Prediction
We propose an unsupervised variational model for disentangling video int...
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11/22/2018
Learning Goal Embeddings via Self-Play for Hierarchical Reinforcement Learning
In hierarchical reinforcement learning a major challenge is determining ...
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03/20/2018
IntPhys: A Framework and Benchmark for Visual Intuitive Physics Reasoning
In order to reach human performance on complex visual tasks, artificial ...
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03/01/2018
Composable Planning with Attributes
The tasks that an agent will need to solve often are not known during tr...
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02/26/2018
Modeling Others using Oneself in Multi-Agent Reinforcement Learning
We consider the multi-agent reinforcement learning setting with imperfec...
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02/21/2018
Stochastic Video Generation with a Learned Prior
Generating video frames that accurately predict future world states is c...
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12/04/2017
Learning by Asking Questions
We introduce an interactive learning framework for the development and t...
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11/19/2016
Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks
We introduce a simple semi-supervised learning approach for images based...
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03/03/2016
Learning Physical Intuition of Block Towers by Example
Wooden blocks are a common toy for infants, allowing them to develop mot...
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12/07/2015
Simple Baseline for Visual Question Answering
We describe a very simple bag-of-words baseline for visual question answ...
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11/23/2015
MazeBase: A Sandbox for Learning from Games
This paper introduces MazeBase: an environment for simple 2D games, desi...
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11/23/2015
Learning Simple Algorithms from Examples
We present an approach for learning simple algorithms such as copying, m...
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06/18/2015
Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks
In this paper we introduce a generative parametric model capable of prod...
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03/31/2015
End-To-End Memory Networks
We introduce a neural network with a recurrent attention model over a po...
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01/23/2015
Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues
We explore the task of recognizing peoples' identities in photo albums i...
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12/02/2014
Learning Spatiotemporal Features with 3D Convolutional Networks
We propose a simple, yet effective approach for spatiotemporal feature l...
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11/19/2014
End-to-End Integration of a Convolutional Network, Deformable Parts Model and Non-Maximum Suppression
Deformable Parts Models and Convolutional Networks each have achieved no...
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11/18/2014
Predicting Depth, Surface Normals and Semantic Labels with a Common Multi-Scale Convolutional Architecture
In this paper we address three different computer vision tasks using a s...
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07/02/2014
Deep Poselets for Human Detection
We address the problem of detecting people in natural scenes using a par...
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06/09/2014
Depth Map Prediction from a Single Image using a Multi-Scale Deep Network
Predicting depth is an essential component in understanding the 3D geome...
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06/09/2014
Training Convolutional Networks with Noisy Labels
The availability of large labeled datasets has allowed Convolutional Net...
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04/02/2014
Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation
We present techniques for speeding up the test-time evaluation of large ...
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12/21/2013
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
We present an integrated framework for using Convolutional Networks for ...
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12/21/2013
Intriguing properties of neural networks
Deep neural networks are highly expressive models that have recently ach...
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12/06/2013
Understanding Deep Architectures using a Recursive Convolutional Network
A key challenge in designing convolutional network models is sizing them...
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11/16/2013
Blind Deconvolution with Non-local Sparsity Reweighting
Blind deconvolution has made significant progress in the past decade. Mo...
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11/12/2013
Visualizing and Understanding Convolutional Networks
Large Convolutional Network models have recently demonstrated impressive...
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01/16/2013
Stochastic Pooling for Regularization of Deep Convolutional Neural Networks
We introduce a simple and effective method for regularizing large convol...
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06/30/2012
