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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
7872019
Continual learning with hypernetworks
J von Oswald, C Henning, BF Grewe, J Sacramento
International Conference on Learning Representations (ICLR 2020), 2019
3082019
Dendritic cortical microcircuits approximate the backpropagation algorithm
J Sacramento, RP Costa, Y Bengio, W Senn
Advances in Neural Information Processing Systems 31, 2018
2932018
Transformers learn in-context by gradient descent
J von Oswald, E Niklasson, E Randazzo, J Sacramento, A Mordvintsev, ...
International Conference on Machine Learning (ICML 2023), 2022
1072022
A Theoretical Framework for Target Propagation
A Meulemans, FS Carzaniga, JAK Suykens, J Sacramento, BF Grewe
Advances in Neural Information Processing Systems 33, 2020
582020
Dendritic error backpropagation in deep cortical microcircuits
J Sacramento, RP Costa, Y Bengio, W Senn
arXiv preprint arXiv:1801.00062, 2017
462017
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
402021
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
382021
Meta-learning via hypernetworks
D Zhao, S Kobayashi, J Sacramento, J von Oswald
NeurIPS Workshop on Meta-learning 2020, 2020
362020
Computational roles of plastic probabilistic synapses
M Llera-Montero, J Sacramento, RP Costa
Current Opinion in Neurobiology 54, 90-97, 2019
282019
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
242021
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
242018
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
212020
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
202016
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
182022
Beyond backpropagation: bilevel optimization through implicit differentiation and equilibrium propagation
N Zucchet, J Sacramento
Neural Computation, 2022
16*2022
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
162018
Energy efficient sparse connectivity from imbalanced synaptic plasticity rules
J Sacramento, A Wichert, MCW van Rossum
PLoS computational biology 11 (6), e1004265, 2015
162015
The least-control principle for local learning at equilibrium
A Meulemans, N Zucchet, S Kobayashi, J von Oswald, J Sacramento
Advances in Neural Information Processing Systems 35, 2022
12*2022
Tree-like hierarchical associative memory structures
J Sacramento, A Wichert
Neural Networks 24 (2), 143-147, 2011
122011
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Articles 1–20