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Sebastian Goldt
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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
201*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
1542021
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
1422019
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
119*2022
Stochastic thermodynamics of resetting
J Fuchs*, S Goldt*, U Seifert
EPL (Europhysics Letters) 113 (6), 60009, 2016
1162016
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
732021
Stochastic thermodynamics of learning
S Goldt, U Seifert
Physical review letters 118 (1), 010601, 2017
652017
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
482021
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
39*2021
Data-driven emergence of convolutional structure in neural networks
A Ingrosso, S Goldt
Proceedings of the National Academy of Sciences 119 (40), e2201854119, 2022
282022
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
192013
Neural networks trained with SGD learn distributions of increasing complexity
M Refinetti, A Ingrosso, S Goldt
International Conference on Machine Learning, 28843-28863, 2023
162023
Thermodynamic efficiency of learning a rule in neural networks
S Goldt, U Seifert
New Journal of Physics 19 (11), 113001, 2017
162017
Perspectives on adaptive dynamical systems
J Sawicki, R Berner, SAM Loos, M Anvari, R Bader, W Barfuss, N Botta, ...
Chaos 33, 071501, 2023
132023
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
122019
The dynamics of representation learning in shallow, non-linear autoencoders
M Refinetti, S Goldt
International Conference on Machine Learning 18499-18519, 2022
112022
Redundant representations help generalization in wide neural networks
D Doimo, A Glielmo, S Goldt, A Laio
Advances in Neural Information Processing Systems 35, in press, 2022
9*2022
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
82022
A simple linear algebra identity to optimize large-scale neural network quantum states
R Rende, LL Viteritti, L Bardone, F Becca, S Goldt
arXiv preprint arXiv:2310.05715, 2023
72023
Role of the potential landscape on the single-file diffusion through channels
SD Goldt, EM Terentjev
The Journal of Chemical Physics 141 (22), 2014
62014
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20