activity
20152019
most citedThe Kinetics Human Action Video Dataset

2.9k citations · 5.3k across the 7 of their papers we have counts for

collaborators

7 papers

cs.NE20196 cited

Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods

Karel Lenc, Erich Elsen, Tom Schaul +1

In this work we show that Evolution Strategies (ES) are a viable method for learning non-differentiable parameters of large supervised models. ES are black-box optimization algorit…

cs.AI20171.1k cited

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

David Silver, Thomas Hubert, Julian Schrittwieser +10

The game of chess is the most widely-studied domain in the history of artificial intelligence. The strongest programs are based on a combination of sophisticated search techniques,…

cs.LG2017343 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…

cs.LG2017249 cited

Population Based Training of Neural Networks

Max Jaderberg, Valentin Dalibard, Simon Osindero +9

Neural networks dominate the modern machine learning landscape, but their training and success still suffer from sensitivity to empirical choices of hyperparameters such as model a…

cs.LG2017682 cited

StarCraft II: A New Challenge for Reinforcement Learning

Oriol Vinyals, Timo Ewalds, Sergey Bartunov +22

This paper introduces SC2LE (StarCraft II Learning Environment), a reinforcement learning environment based on the StarCraft II game. This domain poses a new grand challenge for re…

cs.CV20172.9k cited

The Kinetics Human Action Video Dataset

Will Kay, Joao Carreira, Karen Simonyan +9

We describe the DeepMind Kinetics human action video dataset. The dataset contains 400 human action classes, with at least 400 video clips for each action. Each clip lasts around 1…