Handbook of LHC Higgs cross sections: 4. Deciphering the nature of the Higgs sector D de Florian, C Grojean, F Maltoni, C Mariotti, A Nikitenko, M Pieri, ...
Cornell University, 2016
2076 * 2016 The frontier of simulation-based inference K Cranmer, J Brehmer, G Louppe
Proceedings of the National Academy of Sciences 117 (48), 30055-30062, 2020
1127 2020 Constraining effective field theories with machine learning J Brehmer, K Cranmer, G Louppe, J Pavez
Physical Review Letters 121 (11), 111801, 2018
210 2018 Mining gold from implicit models to improve likelihood-free inference J Brehmer, G Louppe, J Pavez, K Cranmer
Proceedings of the National Academy of Sciences, 2020, 2018
200 2018 A guide to constraining effective field theories with machine learning J Brehmer, K Cranmer, G Louppe, J Pavez
Physical Review D 98 (5), 052004, 2018
194 2018 Flows for simultaneous manifold learning and density estimation J Brehmer, K Cranmer
34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020), 2020
180 2020 MadMiner: Machine learning-based inference for particle physics J Brehmer, F Kling, I Espejo, K Cranmer
Computing and Software for Big Science 4 (1), 3, 2020
148 2020 Weakly supervised causal representation learning J Brehmer, P De Haan, P Lippe, T Cohen
36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022), 2022
144 2022 Pushing Higgs effective theory to its limits J Brehmer, A Freitas, D Lopez-Val, T Plehn
Physical Review D 93 (7), 075014, 2016
141 2016 Simulation intelligence: Towards a new generation of scientific methods A Lavin, H Zenil, B Paige, D Krakauer, J Gottschlich, T Mattson, ...
arXiv preprint arXiv:2112.03235, 2021
135 2021 Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning J Brehmer, S Mishra-Sharma, J Hermans, G Louppe, K Cranmer
The Astrophysical Journal 886 (1), 49, 2019
119 2019 Symmetry Restored in Dibosons at the LHC? J Brehmer, JA Hewett, J Kopp, T Rizzo, J Tattersall
Journal of High Energy Physics 2015 (10), 1-32, 2015
99 2015 Better Higgs- J Brehmer, F Kling, T Plehn, TMP Tait
Physical Review D 97 (9), 095017, 2018
85 2018 Better Higgs boson measurements through information geometry J Brehmer, K Cranmer, F Kling, T Plehn
Physical Review D 95 (7), 073002, 2017
84 2017 Extending the limits of Higgs effective theory A Biekötter, J Brehmer, T Plehn
Physical Review D 94 (5), 055032, 2016
66 2016 Implicit neural video compression Y Zhang, T van Rozendaal, J Brehmer, M Nagel, T Cohen
ICLR Workshop on Deep Generative Models for Highly Structured Data, 2022
63 2022 Benchmarking simplified template cross sections in WH production J Brehmer, S Dawson, S Homiller, F Kling, T Plehn
Journal of High Energy Physics 2019 (11), 1-30, 2019
59 2019 Neural Message Passing for Jet Physics I Henrion, J Brehmer, J Bruna, K Cho, K Cranmer, G Louppe, G Rochette
NIPS Workshop on Deep Learning for the Physical Sciences 2017, 2017
56 * 2017 Geometric Algebra Transformer J Brehmer, P De Haan, S Behrends, T Cohen
37th Annual Conference on Neural Information Processing Systems (NeurIPS 2023), 2023
55 2023 Likelihood-free inference with an improved cross-entropy estimator M Stoye, J Brehmer, G Louppe, J Pavez, K Cranmer
NeurIPS Workshop on Machine Learning for the Physical Sciences 2019, 2018
53 2018 
Kyle CranmerUniversity of Wisconsin-MadisonZweryfikowany adres z wisc.edu