Sebastian Goldt

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Florent KrzakalaÉcole polytechnique fédérale de LausanneVerified email at epfl.ch
Lenka ZdeborováEPFL, SwitzerlandVerified email at epfl.ch
Marc MezardBocconi University MilanoVerified email at unibocconi.it
Andrew SaxeProfessor, Gatsby Unit & Sainsbury Wellcome Centre, UCLVerified email at ucl.ac.uk
Maria RefinettiEcole Normale Supérieure de ParisVerified email at ens.fr
Riccardo RendePhD Student @ SISSAVerified email at sissa.it
Bruno LoureiroÉcole Normale Supérieure & CNRSVerified email at di.ens.fr
Udo SeifertProfessor of Theoretical Physics, University of StuttgartVerified email at theo2.physik.uni-stuttgart.de
Galen ReevesDuke UniversityVerified email at duke.edu
Alessandro IngrossoAssistant Professor, Radboud UniversityVerified email at donders.ru.nl
Federico BeccaUniversity of TriesteVerified email at units.it
Sebastian LeeFlatiron InstituteVerified email at flatironinstitute.org
Alessandro LaioSISSAVerified email at sissa.it
Luciano Loris ViterittiPostdoc @ École Polytechnique Fédérale de Lausanne (EPFL)Verified email at epfl.ch
Lorenzo BardonePhd student, International School of Advanced Studies (SISSA), Trieste, ItalyVerified email at sissa.it
Madhu AdvaniHarvard UniversityVerified email at fas.harvard.edu
Federica GeraceAlma Mater Università di BolognaVerified email at unibo.it
Hugo CuiPostdoctoral fellow, Harvard CMSAVerified email at fas.harvard.edu
Jaco FuchsETH ZürichVerified email at phys.ethz.ch
Stefano SARAO MANNELLIAssistant Professor, DSAI CSE, Chalmers University of Technology and Gothenburg UniversityVerified email at chalmers.se

Sebastian Goldt

International School of Advanced Studies (SISSA), Trieste, Italy

Verified email at sissa.it - Homepage

Theory of Neural Networks Machine Learning Computational Neuroscience Stochastic Thermodynamics


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Modelling the influence of data structure on learning in neural networks: the hidden manifold model S Goldt, M Mézard, F Krzakala, L Zdeborová Physical Review X 10 (4), 041044, 2019	251*	2019
Learning curves of generic features maps for realistic datasets with a teacher-student model B Loureiro, C Gerbelot, H Cui, S Goldt, F Krzakala, M Mezard, ... Advances in Neural Information Processing Systems 34, 18137-18151, 2021	202	2021
The gaussian equivalence of generative models for learning with shallow neural networks S Goldt, B Loureiro, G Reeves, F Krzakala, M Mézard, L Zdeborová Mathematical and Scientific Machine Learning, 426-471, 2022	187*	2022
Dynamics of stochastic gradient descent for two-layer neural networks in the teacher-student setup S Goldt, MS Advani, AM Saxe, F Krzakala, L Zdeborová Advances in Neural Information Processing Systems 32, 6979--6989, 2019	183	2019
Stochastic thermodynamics of resetting J Fuchs, S Goldt, U Seifert EPL (Europhysics Letters) 113 (6), 60009, 2016	147	2016
Classifying high-dimensional Gaussian mixtures: Where kernel methods fail and neural networks succeed M Refinetti, S Goldt, F Krzakala, L Zdeborová International Conference on Machine Learning, 8936-8947, 2021	102	2021
Continual learning in the teacher-student setup: Impact of task similarity S Lee, S Goldt, A Saxe International Conference on Machine Learning, 6109-6119, 2021	86	2021
Stochastic thermodynamics of learning S Goldt, U Seifert Physical review letters 118 (1), 010601, 2017	74	2017
Align, then memorise: the dynamics of learning with feedback alignment M Refinetti, S d’Ascoli, R Ohana, S Goldt International Conference on Machine Learning, 8925-8935, 2021	60	2021
A simple linear algebra identity to optimize large-scale neural network quantum states R Rende, LL Viteritti, L Bardone, F Becca, S Goldt Communications Physics 7 (1), 260, 2024	46*	2024
Data-driven emergence of convolutional structure in neural networks A Ingrosso, S Goldt Proceedings of the National Academy of Sciences 119 (40), e2201854119, 2022	46	2022
Neural networks trained with SGD learn distributions of increasing complexity M Refinetti, A Ingrosso, S Goldt International Conference on Machine Learning, 28843-28863, 2023	40	2023
Perspectives on adaptive dynamical systems J Sawicki, R Berner, SAM Loos, M Anvari, R Bader, W Barfuss, N Botta, ... Chaos 33, 071501, 2023	34	2023
Mapping of attention mechanisms to a generalized Potts model R Rende, F Gerace, A Laio, S Goldt Physical Review Research 6 (2), 023057, 2024	31*	2024
Transformer wave function for the shastry-sutherland model: emergence of a spin-liquid phase LL Viteritti, R Rende, A Parola, S Goldt, F Becca arXiv preprint arXiv:2311.16889, 2023	26	2023
The dynamics of representation learning in shallow, non-linear autoencoders M Refinetti, S Goldt International Conference on Machine Learning 18499-18519, 2022	24	2022
Zinc finger proteins and the 3D organization of chromosomes CJ Feinauer, A Hofmann, S Goldt, L Liu, G Mate, DW Heermann Advances in protein chemistry and structural biology 90, 67-117, 2013	19	2013
Maslow's Hammer for Catastrophic Forgetting: Node Re-Use vs Node Activation S Lee, SS Mannelli, C Clopath, S Goldt, A Saxe International Conference on Machine Learning, PMLR 162:12455-12477, 2022	16	2022
Thermodynamic efficiency of learning a rule in neural networks S Goldt, U Seifert New Journal of Physics 19 (11), 113001, 2017	16	2017
Generalisation dynamics of online learning in over-parameterised neural networks S Goldt, MS Advani, AM Saxe, F Krzakala, L Zdeborová ICML 2019 Workshop on Theoretical Physics for Deep Learning, 2019	15	2019

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