The Workshop will be held virtually at, on May 7th.
Time zone: PDT

8:45–9:00AM: Opening remarks

9:00–9:30AM: Invited talk: Nils Thuerey - Differentiable Simulations as Fundamental Building Blocks for Deep Learning

9:30–10:00AM: Invited talk: Larry Zitnick - Open Catalyst Project: using AI to model and discover new catalyst to address the energy challenges posed by climate change

10:00–10:30AM: Invited talk: Shirley Ho - Learning Symbolic Equations with Deep Learning

10:30–11:00AM: Q&A / Discussions / Coffee break 1

11:00–11:15AM: Contributed talks 1: Alvaro Sanchez-Gonzalez, Kimberly Stachenfeld - Learning general-purpose CNN-based simulators for astrophysical turbulence. Poster

11:15–11:30AM: Break

11:30AM–1:00PM: Virtual Poster Session (please enther via this link)

1:00–1:30PM: Invited talk: David Duvenaud - Latent Stochastic Differential Equations

1:30–2:00PM: Invited talk: Anima Anandkumar - AI4Science: a revolution in the making

2:00–2:30PM: Invited talk: Jesse Thaler - Deep Learning for Collider Physics Simulation

2:30–2:45PM: Q&A / Discussions 2

2:45–3:00PM: Contributed talks 2: Andreas Mayr - Learning 3D Granular Flow Simulations. Poster

3:00–3:15PM: Contributed talks 3: Weihua Hu - ForceNet: A Graph Neural Network for Large-Scale Quantum Calculations. Poster

3:15–3:30PM: Break

3:30–4:00PM: Invited talk: Ron Fedkiw - On Neural Networks for Physical Simulation

4:00–4:30PM: Invited talk: Yunzhu Li - Learning Computational Dynamics Models for Physics Inference and Model-based Control.

4:30–4:45PM: Q&A / Discussions 3

4:45–5:00PM: Closing remarks