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07/07/2021
Evaluating Large Language Models Trained on Code
We introduce Codex, a GPT language model fine-tuned on publicly availabl...
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06/02/2021
A Generalizable Approach to Learning Optimizers
A core issue with learning to optimize neural networks has been the lack...
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01/13/2021
Asymmetric self-play for automatic goal discovery in robotic manipulation
We train a single, goal-conditioned policy that can solve many robotic m...
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09/27/2020
Predicting Sim-to-Real Transfer with Probabilistic Dynamics Models
We propose a method to predict the sim-to-real transfer performance of R...
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10/16/2019
Solving Rubik's Cube with a Robot Hand
We demonstrate that models trained only in simulation can be used to sol...
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02/26/2018
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
The purpose of this technical report is two-fold. First of all, it intro...
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10/18/2017
Asymmetric Actor Critic for Image-Based Robot Learning
Deep reinforcement learning (RL) has proven a powerful technique in many...
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10/18/2017
Sim-to-Real Transfer of Robotic Control with Dynamics Randomization
Simulations are attractive environments for training agents as they prov...
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10/17/2017
Domain Randomization and Generative Models for Robotic Grasping
Deep learning-based robotic grasping has made significant progress the p...
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09/28/2017
Overcoming Exploration in Reinforcement Learning with Demonstrations
Exploration in environments with sparse rewards has been a persistent pr...
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07/05/2017
Hindsight Experience Replay
Dealing with sparse rewards is one of the biggest challenges in Reinforc...
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03/21/2017
One-Shot Imitation Learning
Imitation learning has been commonly applied to solve different tasks in...
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11/02/2016
Extensions and Limitations of the Neural GPU
The Neural GPU is a recent model that can learn algorithms such as multi...
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10/11/2016
Transfer from Simulation to Real World through Learning Deep Inverse Dynamics Model
Developing control policies in simulation is often more practical and sa...
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06/10/2016
Improved Techniques for Training GANs
We present a variety of new architectural features and training procedur...
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06/05/2016
OpenAI Gym
OpenAI Gym is a toolkit for reinforcement learning research. It includes...
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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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11/20/2015
Sequence Level Training with Recurrent Neural Networks
Many natural language processing applications use language models to gen...
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06/26/2015
Convolutional networks and learning invariant to homogeneous multiplicative scalings
The conventional classification schemes -- notably multinomial logistic ...
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05/04/2015
Reinforcement Learning Neural Turing Machines - Revised
The Neural Turing Machine (NTM) is more expressive than all previously c...
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10/30/2014
Addressing the Rare Word Problem in Neural Machine Translation
Neural Machine Translation (NMT) is a new approach to machine translatio...
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10/17/2014
Learning to Execute
Recurrent Neural Networks (RNNs) with Long Short-Term Memory units (LSTM...
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09/08/2014
Recurrent Neural Network Regularization
We present a simple regularization technique for Recurrent Neural Networ...
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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
Spectral Networks and Locally Connected Networks on Graphs
Convolutional Neural Networks are extremely efficient architectures in i...
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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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07/08/2013