Disentanglement by nonlinear ICA with general incompressible-flow networks (GIN) P Sorrenson, C Rother, U Köthe International Conference on Learning Representations, 2020 | 139 | 2020 |
Symmetries, safety, and self-supervision BM Dillon, G Kasieczka, H Olischlager, T Plehn, P Sorrenson, L Vogel SciPost Physics 12 (6), 188, 2022 | 72 | 2022 |
Better latent spaces for better autoencoders BM Dillon, T Plehn, C Sauer, P Sorrenson SciPost Physics 11 (3), 061, 2021 | 65 | 2021 |
Jet Diffusion versus JetGPT--Modern Networks for the LHC A Butter, N Huetsch, SP Schweitzer, T Plehn, P Sorrenson, J Spinner arXiv preprint arXiv:2305.10475, 2023 | 42 | 2023 |
Framework for easily invertible architectures (FrEIA) L Ardizzone, T Bungert, F Draxler, U Köthe, J Kruse, R Schmier, ... Source code, 2018 | 41* | 2018 |
A normalized autoencoder for LHC triggers BM Dillon, L Favaro, T Plehn, P Sorrenson, M Krämer SciPost Physics Core 6 (4), 074, 2023 | 31 | 2023 |
Lifting architectural constraints of injective flows P Sorrenson, F Draxler, A Rousselot, S Hummerich, L Zimmermann, ... The Twelfth International Conference on Learning Representations, 2024 | 11* | 2024 |
Free-form flows: Make any architecture a normalizing flow F Draxler, P Sorrenson, L Zimmermann, A Rousselot, U Köthe International Conference on Artificial Intelligence and Statistics, 2197-2205, 2024 | 9 | 2024 |
Jet diffusion versus JetGPT–Modern networks for the LHC,(arXiv preprint) doi: 10.48550 A Butter, N Huetsch, SP Schweitzer, T Plehn, P Sorrenson, J Spinner arXiv preprint arXiv.2305.10475, 0 | 6 | |
Learning Distributions on Manifolds with Free-form Flows P Sorrenson, F Draxler, A Rousselot, S Hummerich, U Köthe Advances in Neural Information Processing Systems, 2024 | 3 | 2024 |
Learning distances from data with normalizing flows and score matching P Sorrenson, D Behrend-Uriarte, C Schnörr, U Köthe arXiv preprint arXiv:2407.09297, 2024 | 1 | 2024 |
Free-Form Flows: Generative Models for Scientific Applications P Sorrenson | | 2025 |
Symmetries and self-supervision in particle physics BM Dillon, G Kasieczka, H Olischläger, T Plehn, P Sorrenson, L Vogel NeurIPS: Machine Learning and the Physical Sciences Workshop, 2021 | | 2021 |