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Nicolas Zucchet
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2020 – today
- 2024
- [i9]Nicolas Zucchet, Antonio Orvieto:
Recurrent neural networks: vanishing and exploding gradients are not the end of the story. CoRR abs/2405.21064 (2024) - 2023
- [c4]Nicolas Zucchet, Robert Meier, Simon Schug, Asier Mujika, João Sacramento:
Online learning of long-range dependencies. NeurIPS 2023 - [i8]Nicolas Zucchet, Robert Meier, Simon Schug, Asier Mujika, João Sacramento:
Online learning of long-range dependencies. CoRR abs/2305.15947 (2023) - [i7]Nicolas Zucchet, Seijin Kobayashi, Yassir Akram, Johannes von Oswald, Maxime Larcher, Angelika Steger, João Sacramento:
Gated recurrent neural networks discover attention. CoRR abs/2309.01775 (2023) - [i6]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 abs/2309.05858 (2023) - 2022
- [j1]Nicolas Zucchet, João Sacramento:
Beyond Backpropagation: Bilevel Optimization Through Implicit Differentiation and Equilibrium Propagation. Neural Comput. 34(12): 2309-2346 (2022) - [c3]Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento:
The least-control principle for local learning at equilibrium. NeurIPS 2022 - [c2]Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento:
A contrastive rule for meta-learning. NeurIPS 2022 - [i5]Nicolas Zucchet, João Sacramento:
Beyond backpropagation: implicit gradients for bilevel optimization. CoRR abs/2205.03076 (2022) - [i4]Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento:
The least-control principle for learning at equilibrium. CoRR abs/2207.01332 (2022) - [i3]Frederik Benzing, Simon Schug, Robert Meier, Johannes von Oswald, Yassir Akram, Nicolas Zucchet, Laurence Aitchison, Angelika Steger:
Random initialisations performing above chance and how to find them. CoRR abs/2209.07509 (2022) - 2021
- [c1]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: 5250-5263 - [i2]Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento:
A contrastive rule for meta-learning. CoRR abs/2104.01677 (2021) - [i1]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 abs/2110.14402 (2021)
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