Graph Networks for Learning Physics

Dez 13, 2019



I'll describe a series of studies that use graph networks to reason about and interact with complex physical systems. These models can be used to predict the motion of bodies in particle systems, infer hidden physical properties, control simulated robotic systems, build physical structures, and interpret the symbolic form of the underlying laws that govern physical systems. More generally, this work underlines graph neural networks' role as a first-class member of the deep learning toolkit.



Über NIPS 2019

Neural Information Processing Systems (NeurIPS) is a multi-track machine learning and computational neuroscience conference that includes invited talks, demonstrations, symposia and oral and poster presentations of refereed papers. Following the conference, there are workshops which provide a less formal setting.

Präsentation speichern

Soll diese Präsentation für 1000 Jahre gespeichert werden?

Wie speichern wir Präsentationen?

Ewigspeicher-Fortschrittswert: 0 = 0.0%


Empfohlene Videos

Präsentationen, deren Thema, Kategorie oder Sprecher:in ähnlich sind

Interessiert an Vorträgen wie diesem? NIPS 2019 folgen