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05/28/2023
Geometric Algebra Transformers
Problems involving geometric data arise in a variety of fields, includin...
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03/22/2023
EDGI: Equivariant Diffusion for Planning with Embodied Agents
Embodied agents operate in a structured world, often solving tasks with ...
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12/09/2022
Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall
Computational fluid dynamics (CFD) is a valuable asset for patient-speci...
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11/04/2022
Deconfounded Imitation Learning
Standard imitation learning can fail when the expert demonstrators have ...
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07/01/2022
Learning Lattice Quantum Field Theories with Equivariant Continuous Flows
We propose a novel machine learning method for sampling from the high-di...
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03/30/2022
Weakly supervised causal representation learning
Learning high-level causal representations together with a causal model ...
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10/06/2021
Scaling Up Machine Learning For Quantum Field Theory with Equivariant Continuous Flows
We propose a continuous normalizing flow for sampling from the high-dime...
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09/10/2021
Mesh convolutional neural networks for wall shear stress estimation in 3D artery models
Computational fluid dynamics (CFD) is a valuable tool for personalised, ...
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07/16/2020
Natural Graph Networks
Conventional neural message passing algorithms are invariant under permu...
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03/11/2020
Gauge Equivariant Mesh CNNs: Anisotropic convolutions on geometric graphs
A common approach to define convolutions on meshes is to interpret them ...
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06/06/2019
Covariance in Physics and Convolutional Neural Networks
In this proceeding we give an overview of the idea of covariance (or equ...
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05/28/2019
Causal Confusion in Imitation Learning
Behavioral cloning reduces policy learning to supervised learning by tra...
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03/07/2019
Reparameterizing Distributions on Lie Groups
Reparameterizable densities are an important way to learn probability di...
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12/27/2018
Topological Constraints on Homeomorphic Auto-Encoding
When doing representation learning on data that lives on a known non-tri...
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07/12/2018