activity
20192024
most citedLearned Coarse Models for Efficient Turbulence Simulation

26 citations · 54 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2024★ 1 cited

Learning rigid-body simulators over implicit shapes for large-scale scenes and vision

Yulia Rubanova, Tatiana Lopez-Guevara, Kelsey R. Allen +3

Simulating large scenes with many rigid objects is crucial for a variety of applications, such as robotics, engineering, film and video games. Rigid interactions are notoriously ha…

cs.LG2024

Scaling Face Interaction Graph Networks to Real World Scenes

Tatiana Lopez-Guevara, Yulia Rubanova, William F. Whitney +3

Accurately simulating real world object dynamics is essential for various applications such as robotics, engineering, graphics, and design. To better capture complex real dynamics…

cs.LG2023★ 1 cited

Learning 3D Particle-based Simulators from RGB-D Videos

William F. Whitney, Tatiana Lopez-Guevara, Tobias Pfaff +4

Realistic simulation is critical for applications ranging from robotics to animation. Traditional analytic simulators sometimes struggle to capture sufficiently realistic simulatio…

cs.LG2022★ 17 cited

Physical Design using Differentiable Learned Simulators

Kelsey R. Allen, Tatiana Lopez-Guevara, Kimberly Stachenfeld +4

Designing physical artifacts that serve a purpose - such as tools and other functional structures - is central to engineering as well as everyday human behavior. Though automating…

physics.flu-dyn2021★ 26 cited

Learned Coarse Models for Efficient Turbulence Simulation

Kimberly Stachenfeld, Drummond B. Fielding, Dmitrii Kochkov +7

Turbulence simulation with classical numerical solvers requires high-resolution grids to accurately resolve dynamics. Here we train learned simulators at low spatial and temporal r…

stat.ML2020★ 6 cited

Graph Networks with Spectral Message Passing

Kimberly Stachenfeld, Jonathan Godwin, Peter Battaglia

Graph Neural Networks (GNNs) are the subject of intense focus by the machine learning community for problems involving relational reasoning. GNNs can be broadly divided into spatia…

cs.LG2019★ 1 cited

Object-oriented state editing for HRL

Victor Bapst, Alvaro Sanchez-Gonzalez, Omar Shams +4

We introduce agents that use object-oriented reasoning to consider alternate states of the world in order to more quickly find solutions to problems. Specifically, a hierarchical c…

cs.LG2019★ 2 cited

Structured agents for physical construction

Victor Bapst, Alvaro Sanchez-Gonzalez, Carl Doersch +4

Physical construction---the ability to compose objects, subject to physical dynamics, to serve some function---is fundamental to human intelligence. We introduce a suite of challen…