Graph Networks for Learning Physics

13. Prosinec 2019


O prezentaci

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.



O organizátorovi (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.

Uložení prezentace

Měla by být tato prezentace uložena po dobu 1000 let?

Jak ukládáme prezentace

Pro uložení prezentace do věčného trezoru hlasovalo 0 diváků, což je 0.0 %


Doporučená videa

Prezentace na podobné téma, kategorii nebo přednášejícího

Zajímají Vás podobná videa? Sledujte NIPS 2019