Nicolas Zucchet

18 papers A* 5Journal 13

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	How do language models learn facts? Dynamics, curricula and hallucinations. CoRR Nicolas Zucchet, Jörg Bornschein, Stephanie C. Y. Chan, Andrew K. Lampinen, Razvan Pascanu, Soham De
2025	J	`jnl`	Teaching signal synchronization in deep neural networks with prospective neurons. CoRR Nicolas Zucchet, Qianqian Feng, Axel Laborieux, Friedemann Zenke, Walter Senn, João Sacramento
2025	J	`jnl`	The emergence of sparse attention: impact of data distribution and benefits of repetition. CoRR Nicolas Zucchet, Francesco D'Angelo, Andrew K. Lampinen, Stephanie C. Y. Chan
2024	A*	`conf`	Recurrent neural networks: vanishing and exploding gradients are not the end of the story. NeurIPS Nicolas Zucchet, Antonio Orvieto
2024	J	`jnl`	Recurrent neural networks: vanishing and exploding gradients are not the end of the story. CoRR Nicolas Zucchet, Antonio Orvieto
2023	J	`jnl`	Gated recurrent neural networks discover attention. CoRR Nicolas Zucchet, Seijin Kobayashi, Yassir Akram, Johannes von Oswald, Maxime Larcher, Angelika Steger, João Sacramento
2023	A*	`conf`	Online learning of long-range dependencies. NeurIPS Nicolas Zucchet, Robert Meier, Simon Schug, Asier Mujika, João Sacramento
2023	J	`jnl`	Online learning of long-range dependencies. CoRR Nicolas Zucchet, Robert Meier, Simon Schug, Asier Mujika, João Sacramento
2023	J	`jnl`	Uncovering mesa-optimization algorithms in Transformers. CoRR 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
2022	A*	`conf`	A contrastive rule for meta-learning. NeurIPS Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento
2022	J	`jnl`	Beyond Backpropagation: Bilevel Optimization Through Implicit Differentiation and Equilibrium Propagation. Neural Comput. Nicolas Zucchet, João Sacramento
2022	J	`jnl`	Beyond backpropagation: implicit gradients for bilevel optimization. CoRR Nicolas Zucchet, João Sacramento
2022	J	`jnl`	Random initialisations performing above chance and how to find them. CoRR Frederik Benzing, Simon Schug, Robert Meier, Johannes von Oswald, Yassir Akram, Nicolas Zucchet, Laurence Aitchison, Angelika Steger
2022	J	`jnl`	The least-control principle for learning at equilibrium. CoRR Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento
2022	A*	`conf`	The least-control principle for local learning at equilibrium. NeurIPS Alexander Meulemans, Nicolas Zucchet, Seijin Kobayashi, Johannes von Oswald, João Sacramento
2021	J	`jnl`	A contrastive rule for meta-learning. CoRR Nicolas Zucchet, Simon Schug, Johannes von Oswald, Dominic Zhao, João Sacramento
2021	A*	`conf`	Learning where to learn: Gradient sparsity in meta and continual learning. NeurIPS Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento
2021	J	`jnl`	Learning where to learn: Gradient sparsity in meta and continual learning. CoRR Johannes von Oswald, Dominic Zhao, Seijin Kobayashi, Simon Schug, Massimo Caccia, Nicolas Zucchet, João Sacramento