papers

Publications (5)

cs.CV2017

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…

astro-ph.GA2021

A Deep Learning Approach for Characterizing Major Galaxy Mergers

Skanda Koppula, Victor Bapst, Marc Huertas-Company +15

Fine-grained estimation of galaxy merger stages from observations is a key problem useful for validation of our current theoretical understanding of galaxy formation. To this end,…

cs.AI2020

Game Plan: What AI can do for Football, and What Football can do for AI

Karl Tuyls, Shayegan Omidshafiei, Paul Muller +33

The rapid progress in artificial intelligence (AI) and machine learning has opened unprecedented analytics possibilities in various team and individual sports, including baseball,…

cs.CV2021

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch +26

Over half a million individuals are diagnosed with head and neck cancer each year worldwide. Radiotherapy is an important curative treatment for this disease, but it requires manua…

cond-mat.mtrl-sci2021

Atomistic graph networks for experimental materials property prediction

Tian Xie, Victor Bapst, Alexander L. Gaunt +5

Machine Learning (ML) has the potential to accelerate discovery of new materials and shed light on useful properties of existing materials. A key difficulty when applying ML in Mat…