activity
20172023
most citedCompetition-Level Code Generation with AlphaCode

1k citations · 1.9k across the 7 of their papers we have counts for

collaborators

7 papers

cs.LG2023★ 5 cited

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning

Michaël Mathieu, Sherjil Ozair, Srivatsan Srinivasan +21

StarCraft II is one of the most challenging simulated reinforcement learning environments; it is partially observable, stochastic, multi-agent, and mastering StarCraft II requires…

cs.PL2022★ 1k cited

Competition-Level Code Generation with AlphaCode

Yujia Li, David Choi, Junyoung Chung +23

Programming is a powerful and ubiquitous problem-solving tool. Developing systems that can assist programmers or even generate programs independently could make programming more pr…

cs.CL2022★ 243 cited

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Jack W. Rae, Sebastian Borgeaud, Trevor Cai +77

Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.…

cs.CV2019★ 24 cited

Unsupervised Doodling and Painting with Improved SPIRAL

John F. J. Mellor, Eunbyung Park, Yaroslav Ganin +7

We investigate using reinforcement learning agents as generative models of images (extending arXiv:1804.01118). A generative agent controls a simulated painting environment, and is…

cs.LG2018★ 155 cited

Relational Deep Reinforcement Learning

Vinicius Zambaldi, David Raposo, Adam Santoro +13

We introduce an approach for deep reinforcement learning (RL) that improves upon the efficiency, generalization capacity, and interpretability of conventional approaches through st…

cs.CV2018★ 135 cited

Synthesizing Programs for Images using Reinforced Adversarial Learning

Yaroslav Ganin, Tejas Kulkarni, Igor Babuschkin +2

Advances in deep generative networks have led to impressive results in recent years. Nevertheless, such models can often waste their capacity on the minutiae of datasets, presumabl…

cs.LG2017★ 343 cited

Parallel WaveNet: Fast High-Fidelity Speech Synthesis

Aaron van den Oord, Yazhe Li, Igor Babuschkin +19

The recently-developed WaveNet architecture is the current state of the art in realistic speech synthesis, consistently rated as more natural sounding for many different languages…