Jan T. Offermann

According to our database, Jan T. Offermann authored at least 5 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

19 Parameters Is All You Need: Tiny Neural Networks for Particle Physics.

Alexander Bogatskiy, Timothy Hoffman, Jan T. Offermann

CoRR, 2023

Explainable Equivariant Neural Networks for Particle Physics: PELICAN.

Alexander Bogatskiy, Timothy Hoffman, David W. Miller, Jan T. Offermann, Xiaoyang Liu

CoRR, 2023

2022

PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics.

Alexander Bogatskiy, Timothy Hoffman, David W. Miller, Jan T. Offermann

CoRR, 2022

Symmetry Group Equivariant Architectures for Physics.

Alexander Bogatskiy, Sanmay Ganguly, Thomas Kipf, Risi Kondor, David W. Miller, Daniel Murnane, Jan T. Offermann, Mariel Pettee, Phiala Shanahan, Chase Shimmin, Savannah Thais

CoRR, 2022

2020

Lorentz Group Equivariant Neural Network for Particle Physics.

Alexander Bogatskiy, Brandon M. Anderson, Jan T. Offermann, Marwah Roussi, David W. Miller, Risi Kondor

Proceedings of the 37th International Conference on Machine Learning, 2020