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João Sacramento
João Sacramento
ETH Zurich, Switzerland
Verified email at joaosacramento.com - Homepage
Title
Cited by
Cited by
Year
A deep learning framework for neuroscience
BA Richards, TP Lillicrap, P Beaudoin, Y Bengio, R Bogacz, ...
Nature Neuroscience 22 (11), 1761-1770, 2019
5932019
Dendritic cortical microcircuits approximate the backpropagation algorithm
J Sacramento, RP Costa, Y Bengio, W Senn
Advances in Neural Information Processing Systems 31, 2018
2362018
Continual learning with hypernetworks
J von Oswald, C Henning, BF Grewe, J Sacramento
International Conference on Learning Representations (ICLR 2020), 2019
2152019
A Theoretical Framework for Target Propagation
A Meulemans, FS Carzaniga, JAK Suykens, J Sacramento, BF Grewe
Advances in Neural Information Processing Systems 33, 2020
472020
Dendritic error backpropagation in deep cortical microcircuits
J Sacramento, RP Costa, Y Bengio, W Senn
arXiv preprint arXiv:1801.00062, 2017
442017
Learning where to learn: Gradient sparsity in meta and continual learning
J von Oswald, D Zhao, S Kobayashi, S Schug, M Caccia, N Zucchet, ...
Advances in Neural Information Processing Systems 34, 2021
272021
Computational roles of plastic probabilistic synapses
M Llera-Montero, J Sacramento, RP Costa
Current Opinion in Neurobiology 54, 90-97, 2019
262019
Meta-learning via hypernetworks
D Zhao, S Kobayashi, J Sacramento, J von Oswald
NeurIPS Workshop on Meta-learning 2020, 2020
222020
Approximating the predictive distribution via adversarially-trained hypernetworks
C Henning, J von Oswald, J Sacramento, SC Surace, JP Pfister, ...
NeurIPS Bayesian Deep Learning Workshop 2018, 2018
222018
Posterior Meta-Replay for Continual Learning
C Henning, MR Cervera, F D'Angelo, J von Oswald, R Traber, B Ehret, ...
Advances in Neural Information Processing Systems 34, 2021
202021
Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible
Y Bengio, B Scellier, O Bilaniuk, J Sacramento, W Senn
arXiv preprint arXiv:1606.01651, 2016
172016
Credit Assignment in Neural Networks through Deep Feedback Control
A Meulemans, MT Farinha, JG Ordóñez, PV Aceituno, J Sacramento, ...
Advances in Neural Information Processing Systems 34, 2021
152021
A contrastive rule for meta-learning
N Zucchet, S Schug, J von Oswald, D Zhao, J Sacramento
Advances in Neural Information Processing Systems 35, 2022
132022
Sensory representation of an auditory cued tactile stimulus in the posterior parietal cortex of the mouse
H Mohan, Y Gallero-Salas, S Carta, J Sacramento, B Laurenczy, ...
Scientific reports 8 (1), 7739, 2018
122018
Energy efficient sparse connectivity from imbalanced synaptic plasticity rules
J Sacramento, A Wichert, MCW van Rossum
PLoS computational biology 11 (6), e1004265, 2015
122015
Transformers learn in-context by gradient descent
J von Oswald, E Niklasson, E Randazzo, J Sacramento, A Mordvintsev, ...
arXiv preprint arXiv:2212.07677, 2022
112022
Neural networks with late-phase weights
J von Oswald, S Kobayashi, A Meulemans, C Henning, BF Grewe, ...
International Conference on Learning Representations (ICLR 2021), 2020
112020
Tree-like hierarchical associative memory structures
J Sacramento, A Wichert
Neural Networks 24 (2), 143-147, 2011
102011
Lagrangian dynamics of dendritic microcircuits enables real-time backpropagation of errors
D Dold, AF Kungl, J Sacramento, MA Petrovici, K Schindler, J Binas, ...
target 100 (1), 2, 2019
72019
Beyond backpropagation: bilevel optimization through implicit differentiation and equilibrium propagation
N Zucchet, J Sacramento
Neural Computation, 2022
6*2022
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