Johannes Brandstetter

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Sepp HochreiterInstitute for Machine Learning, Johannes Kepler University LinzAdresse e-mail validée de ml.jku.at
Günter KlambauerProf., LIT AI Lab & Institute for Machine Learning, Johannes Kepler UniversityAdresse e-mail validée de ml.jku.at
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamAdresse e-mail validée de uva.nl
Michael WidrichMachine Learning Scientist @ FreenomeAdresse e-mail validée de freenome.com
Jayesh K. GuptaSilurianAdresse e-mail validée de cs.stanford.edu
Hubert RamsauerResearch Assistant at Institute for Machine Learning, Johannes Kepler University LinzAdresse e-mail validée de ml.jku.at
Daniel WorrallUniversity of AmsterdamAdresse e-mail validée de deepmind.com
Benedikt AlkinPhD Student, Johannes Kepler UniversityAdresse e-mail validée de ml.jku.at
Andreas MayrInstitute for Machine Learning, Johannes Kepler University LinzAdresse e-mail validée de ml.jku.at
Elise van der PolMicrosoft ResearchAdresse e-mail validée de microsoft.com
Phillip LippePhD Student, University of AmsterdamAdresse e-mail validée de uva.nl
David RuheUniversity of AmsterdamAdresse e-mail validée de uva.nl
Vihang PatilInstitute for Machine Learning, JKU, LinzAdresse e-mail validée de ml.jku.at
Ashish KapoorCEO and Chief Scientist, Scaled FoundationsAdresse e-mail validée de scaledfoundations.ai
Artur P. ToshevTechnical University of MunichAdresse e-mail validée de tum.de
Erik J BekkersUniversity of AmsterdamAdresse e-mail validée de uva.nl
Ana LučićUniversity of AmsterdamAdresse e-mail validée de uva.nl
Patrick ForréAssociate Professor Machine Learning, AI4Science Lab Manager, University of AmsterdamAdresse e-mail validée de uva.nl
Rianne van den BergPrincipal Research Manager, Microsoft ResearchAdresse e-mail validée de microsoft.com
Tung NguyenPhD student at UCLAAdresse e-mail validée de cs.ucla.edu

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Johannes Brandstetter

Johannes Kepler University (JKU) Linz

Adresse e-mail validée de ml.jku.at - Page d'accueil

Machine Learning Deep Learning AI4Science Physically-based simulation Physics


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Combined measurements of Higgs boson couplings in proton–proton collisions at CMS Collaboration The European Physical Journal C 79 (5), 1-44, 2019	986*	2019
Performance of missing transverse momentum reconstruction in proton-proton collisions at√ s= 13 TeV using the CMS detector CMS Collaboration Journal of Instrumentation, 2019	875*	2019
Observation of the Higgs boson decay to a pair of tau leptons with the CMS detector CMS Collaboration Phys. Lett. B 779, 283-316, 2017	707*	2017
Hopfield networks is all you need H Ramsauer, B Schäfl, J Lehner, P Seidl, M Widrich, T Adler, L Gruber, ... 9th International Conference on Learning Representations (ICLR 2021), 2020	605	2020
Technical proposal for the Phase-II upgrade of the Compact Muon Solenoid CMS Collaboration CMS Technical Proposal CERN-LHCC-2015-010, CMS-TDR-15-02, 2015	492	2015
Search for additional neutral MSSM Higgs bosons in the final state in proton-proton collisions at 13 TeV CMS Collaboration Journal of High Energy Physics 9, 1-60, 2018	373*	2018
Message passing neural PDE solvers J Brandstetter, D Worrall, M Welling 10th International Conference on Learning Representations (ICLR 2022), 2022	325	2022
ClimaX: A foundation model for weather and climate T Nguyen, J Brandstetter, A Kapoor, JK Gupta, A Grover Proceedings of the 40th International Conference on Machine Learning 202 …, 2023	293*	2023
Rudder: Return decomposition for delayed rewards JA Arjona-Medina, M Gillhofer, M Widrich, T Unterthiner, J Brandstetter, ... Advances in Neural Information Processing Systems 32, 2019	284	2019
Geometric and Physical Quantities improve E (3) Equivariant Message Passing J Brandstetter, R Hesselink, E van der Pol, E Bekkers, M Welling 10th International Conference on Learning Representations (ICLR 2022), 2021	242	2021
Measurement of prompt J/ψ pair production in pp collisions at = 7 Tev CMS Collaboration Journal of High Energy Physics 2014 (9), 1-35, 2014	220*	2014
Performance of reconstruction and identification of tau leptons in their decays to hadrons and tau neutrino in LHC Run-2 CMS Collaboration CMS-PAS-TAU-16-002, 2016	216*	2016
xLSTM: Extended Long Short-Term Memory M Beck, K Pöppel, M Spanring, A Auer, O Prudnikova, M Kopp, ... arXiv preprint arXiv:2405.04517, 2024	174	2024
Modern hopfield networks and attention for immune repertoire classification M Widrich, B Schäfl, M Pavlović, H Ramsauer, L Gruber, M Holzleitner, ... Advances in neural information processing systems 33, 18832-18845, 2020	152*	2020
Uncertainty estimation with deep learning for rainfall–runoff modelling D Klotz, F Kratzert, M Gauch, A Keefe Sampson, J Brandstetter, ... Hydrology and Earth System Sciences Discussions 2021, 1-32, 2021	131	2021
Search for a singly produced third-generation scalar leptoquark decaying to a τ lepton and a bottom quark in proton-proton collisions at s= 13 TeV CMS Collaboration Journal of High Energy Physics 2018 (7), 1-40, 2018	129	2018
Towards multi-spatiotemporal-scale generalized pde modeling JK Gupta, J Brandstetter Transactions on Machine Learning (TMLR) 07/2023, 2022	117	2022
Clifford neural layers for PDE modeling J Brandstetter, R Berg, M Welling, JK Gupta 11th International Conference on Learning Representations (ICLR 2023), 2022	107	2022
Measurement of the cross section in pp collisions at and validation of lepton analysis techniques CMS Collaboration European Physical Journal. C, Particles and Fields 78 (FERMILAB-PUB-18-010 …, 2018	72*	2018
Pde-refiner: Achieving accurate long rollouts with neural pde solvers P Lippe, BS Veeling, P Perdikaris, RE Turner, J Brandstetter Advances in Neural Information Processing Systems 36, 2023	71*	2023

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