research
∙
05/28/2023
Geometric Algebra Transformers
Problems involving geometric data arise in a variety of fields, includin...
share
research
∙
03/22/2023
EDGI: Equivariant Diffusion for Planning with Embodied Agents
Embodied agents operate in a structured world, often solving tasks with ...
research
∙
11/04/2022
Deconfounded Imitation Learning
Standard imitation learning can fail when the expert demonstrators have ...
research
∙
03/30/2022
Weakly supervised causal representation learning
Learning high-level causal representations together with a causal model ...
research
∙
12/21/2021
Implicit Neural Video Compression
We propose a method to compress full-resolution video sequences with imp...
research
∙
12/06/2021
Simulation Intelligence: Towards a New Generation of Scientific Methods
The original "Seven Motifs" set forth a roadmap of essential methods for...
research
∙
11/19/2021
Instance-Adaptive Video Compression: Improving Neural Codecs by Training on the Test Set
We introduce a video compression algorithm based on instance-adaptive le...
research
∙
11/16/2020
Hierarchical clustering in particle physics through reinforcement learning
Particle physics experiments often require the reconstruction of decay p...
research
∙
10/13/2020
Simulation-based inference methods for particle physics
Our predictions for particle physics processes are realized in a chain o...
research
∙
03/31/2020
Flows for simultaneous manifold learning and density estimation
We introduce manifold-modeling flows (MFMFs), a new class of generative ...
research
∙
11/04/2019
The frontier of simulation-based inference
Many domains of science have developed complex simulations to describe p...
research
∙
09/04/2019
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning
The subtle and unique imprint of dark matter substructure on extended ar...
research
∙
07/24/2019
MadMiner: Machine learning-based inference for particle physics
The legacy measurements of the LHC will require analyzing high-dimension...
research
∙
06/04/2019
Effective LHC measurements with matrix elements and machine learning
One major challenge for the legacy measurements at the LHC is that the l...
research
∙
08/02/2018
Likelihood-free inference with an improved cross-entropy estimator
We extend recent work (Brehmer, et. al., 2018) that use neural networks ...
research
∙
05/30/2018
Mining gold from implicit models to improve likelihood-free inference
Simulators often provide the best description of real-world phenomena; h...
research
∙
04/30/2018
A Guide to Constraining Effective Field Theories with Machine Learning
We develop, discuss, and compare several inference techniques to constra...
research
∙
04/30/2018
