João Sacramento

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 38

Top Topics

Backpropagation Algorithm

Mathematical Program

Biologically Plausible

Top Venues

Publications

Simon Schug, Seijin Kobayashi, Yassir Akram, João Sacramento, Razvan Pascanu
Attention as a Hypernetwork. CoRR (2024)
Seijin Kobayashi, Simon Schug, Yassir Akram, Florian Redhardt, Johannes von Oswald, Razvan Pascanu, Guillaume Lajoie, João Sacramento
When can transformers compositionally generalize in-context? CoRR (2024)
Maciej Pióro, Maciej Wolczyk, Razvan Pascanu, Johannes von Oswald, João Sacramento
State Soup: In-Context Skill Learning, Retrieval and Mixing. CoRR (2024)
Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Proca, Johannes von Oswald, Razvan Pascanu, João Sacramento, Angelika Steger
Discovering modular solutions that generalize compositionally. ICLR (2024)
Nicolas Zucchet, Robert Meier, Simon Schug, Asier Mujika, João Sacramento
Online learning of long-range dependencies. NeurIPS (2023)
Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Proca, Johannes von Oswald, Razvan Pascanu, João Sacramento, Angelika Steger
Discovering modular solutions that generalize compositionally. CoRR (2023)
Nicolas Zucchet, Seijin Kobayashi, Yassir Akram, Johannes von Oswald, Maxime Larcher, Angelika Steger, João Sacramento
Gated recurrent neural networks discover attention. CoRR (2023)
Johannes von Oswald, Eyvind Niklasson, Maximilian Schlegel, Seijin Kobayashi, Nicolas Zucchet, Nino Scherrer, Nolan Miller, Mark Sandler, Blaise Agüera y Arcas, Max Vladymyrov, Razvan Pascanu, João Sacramento
Uncovering mesa-optimization algorithms in Transformers. CoRR (2023)
Nicolas Zucchet, Robert Meier, Simon Schug, Asier Mujika, João Sacramento
Online learning of long-range dependencies. CoRR (2023)
Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, João Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, Max Vladymyrov
Transformers Learn In-Context by Gradient Descent. ICML (2023)
Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento
The least-control principle for local learning at equilibrium. NeurIPS (2022)
Alexander Meulemans, Matilde Tristany Farinha, Maria R. Cervera, João Sacramento, Benjamin F. Grewe
Minimizing Control for Credit Assignment with Strong Feedback. ICML (2022)
Alexander Meulemans, Matilde Tristany Farinha, Maria R. Cervera, João Sacramento, Benjamin F. Grewe
Minimizing Control for Credit Assignment with Strong Feedback. CoRR (2022)
Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento
The least-control principle for learning at equilibrium. CoRR (2022)
Nicolas Zucchet, João Sacramento
Beyond backpropagation: implicit gradients for bilevel optimization. CoRR (2022)
Johannes von Oswald, Eyvind Niklasson, Ettore Randazzo, João Sacramento, Alexander Mordvintsev, Andrey Zhmoginov, Max Vladymyrov
Transformers learn in-context by gradient descent. CoRR (2022)
Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento
A contrastive rule for meta-learning. NeurIPS (2022)
Nicolas Zucchet, João Sacramento
Beyond Backpropagation: Bilevel Optimization Through Implicit Differentiation and Equilibrium Propagation. Neural Comput. 34 (12) (2022)
Christian Henning, Maria R. Cervera, Francesco D'Angelo, Johannes von Oswald, Regina Traber, Benjamin Ehret, Seijin Kobayashi, João Sacramento, Benjamin F. Grewe
Posterior Meta-Replay for Continual Learning. CoRR (2021)
Johannes von Oswald, Seijin Kobayashi, João Sacramento, Alexander Meulemans, Christian Henning, Benjamin F. Grewe
Neural networks with late-phase weights. ICLR (2021)
Christian Henning, Maria R. Cervera, Francesco D'Angelo, Johannes von Oswald, Regina Traber, Benjamin Ehret, Seijin Kobayashi, Benjamin F. Grewe, João Sacramento
Posterior Meta-Replay for Continual Learning. NeurIPS (2021)
Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento
Learning where to learn: Gradient sparsity in meta and continual learning. NeurIPS (2021)
Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento
A contrastive rule for meta-learning. CoRR (2021)
Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe
Credit Assignment in Neural Networks through Deep Feedback Control. NeurIPS (2021)
Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento
Learning where to learn: Gradient sparsity in meta and continual learning. CoRR (2021)
Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe
Credit Assignment in Neural Networks through Deep Feedback Control. CoRR (2021)
Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens, João Sacramento, Benjamin F. Grewe
A Theoretical Framework for Target Propagation. NeurIPS (2020)
Jakob Jordan, Mihai A. Petrovici, Walter Senn, João Sacramento
Conductance-based dendrites perform reliability-weighted opinion pooling. NICE (2020)
Alexander Meulemans, Francesco S. Carzaniga, Johan A. K. Suykens, João Sacramento, Benjamin F. Grewe
A Theoretical Framework for Target Propagation. CoRR (2020)
Johannes von Oswald, Christian Henning, João Sacramento, Benjamin F. Grewe
Continual learning with hypernetworks. ICLR (2020)
João Sacramento, Johannes von Oswald, Seijin Kobayashi, Christian Henning, Benjamin F. Grewe
Economical ensembles with hypernetworks. CoRR (2020)
Thomas Mesnard, Gaëtan Vignoud, João Sacramento, Walter Senn, Yoshua Bengio
Ghost Units Yield Biologically Plausible Backprop in Deep Neural Networks. CoRR (2019)
Johannes von Oswald, Christian Henning, João Sacramento, Benjamin F. Grewe
Continual learning with hypernetworks. CoRR (2019)
João Sacramento, Rui Ponte Costa, Yoshua Bengio, Walter Senn
Dendritic error backpropagation in deep cortical microcircuits. CoRR (2018)
João Sacramento, Rui Ponte Costa, Yoshua Bengio, Walter Senn
Dendritic cortical microcircuits approximate the backpropagation algorithm. NeurIPS (2018)
João Sacramento, Rui Ponte Costa, Yoshua Bengio, Walter Senn
Dendritic cortical microcircuits approximate the backpropagation algorithm. CoRR (2018)
Yoshua Bengio, Benjamin Scellier, Olexa Bilaniuk, João Sacramento, Walter Senn
Feedforward Initialization for Fast Inference of Deep Generative Networks is biologically plausible. CoRR (2016)
João Sacramento, Andreas Wichert, Mark C. W. van Rossum
Energy Efficient Sparse Connectivity from Imbalanced Synaptic Plasticity Rules. PLoS Comput. Biol. 11 (6) (2015)
Diogo Rendeiro, João Sacramento, Andreas Wichert
Taxonomical Associative Memory. Cogn. Comput. 6 (1) (2014)
João Sacramento, Andreas Wichert
Binary Willshaw learning yields high synaptic capacity for long-term familiarity memory. Biol. Cybern. 106 (2) (2012)
João Sacramento, Francisco Burnay, Andreas Wichert
Regarding the temporal requirements of a hierarchical Willshaw network. Neural Networks 25 (2012)
João Sacramento, Andreas Wichert
Tree-like hierarchical associative memory structures. Neural Networks 24 (2) (2011)