research
∙
11/18/2022
Exploring through Random Curiosity with General Value Functions
Efficient exploration in reinforcement learning is a challenging problem...
share
research
∙
11/04/2022
The Benefits of Model-Based Generalization in Reinforcement Learning
Model-Based Reinforcement Learning (RL) is widely believed to have the p...
research
∙
07/04/2022
Goal-Conditioned Generators of Deep Policies
Goal-conditioned Reinforcement Learning (RL) aims at learning optimal po...
research
∙
07/04/2022
General Policy Evaluation and Improvement by Learning to Identify Few But Crucial States
Learning to evaluate and improve policies is a core problem of Reinforce...
research
∙
04/13/2022
Hierarchical Text-Conditional Image Generation with CLIP Latents
Contrastive models like CLIP have been shown to learn robust representat...
research
∙
12/20/2021
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Diffusion models have recently been shown to generate high-quality synth...
research
∙
10/11/2021
Unsupervised Neural Machine Translation with Generative Language Models Only
We show how to derive state-of-the-art unsupervised neural machine trans...
research
∙
02/26/2021
Learning Transferable Visual Models From Natural Language Supervision
State-of-the-art computer vision systems are trained to predict a fixed ...
research
∙
02/24/2021
Zero-Shot Text-to-Image Generation
Text-to-image generation has traditionally focused on finding better mod...
research
∙
10/28/2020
Scaling Laws for Autoregressive Generative Modeling
We identify empirical scaling laws for the cross-entropy loss in four do...
research
∙
07/09/2020
Recurrent Neural-Linear Posterior Sampling for Non-Stationary Contextual Bandits
An agent in a non-stationary contextual bandit problem should balance be...
research
∙
06/14/2020
CompressNet: Generative Compression at Extremely Low Bitrates
Compressing images at extremely low bitrates (< 0.1 bpp) has always been...
research
∙
05/28/2020
Language Models are Few-Shot Learners
Recent work has demonstrated substantial gains on many NLP tasks and ben...
research
∙
12/04/2018
A Spectral Regularizer for Unsupervised Disentanglement
Generative models that learn to associate variations in the output along...
research
∙
07/23/2018
Clustering of Driving Scenarios Using Connected Vehicle Datasets
Driving encounter classification and analysis can benefit autonomous veh...
research
∙
06/01/2018
Backpropagation for Implicit Spectral Densities
Most successful machine intelligence systems rely on gradient-based lear...
research
∙
11/10/2016
