Seijin Kobayashi

31 papers A* 11Journal 20

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Attention as a Hypernetwork. ICLR Simon Schug, Seijin Kobayashi, Yassir Akram, João Sacramento, Razvan Pascanu
2025	J	`jnl`	Embedded Universal Predictive Intelligence: a coherent framework for multi-agent learning. CoRR Alexander Meulemans, Rajai Nasser, Maciej Wolczyk, Marissa A. Weis, Seijin Kobayashi, Blake A. Richards, Guillaume Lajoie, Angelika Steger, Marcus Hutter, James Manyika, Rif A. Saurous, João Sacramento, Blaise Agüera y Arcas
2025	J	`jnl`	Emergent temporal abstractions in autoregressive models enable hierarchical reinforcement learning. CoRR Seijin Kobayashi, Yanick Schimpf, Maximilian Schlegel, Angelika Steger, Maciej Wolczyk, Johannes von Oswald, Nino Scherrer, Kaitlin Maile, Guillaume Lajoie, Blake A. Richards, Rif A. Saurous, James Manyika, Blaise Agüera y Arcas, Alexander Meulemans, João Sacramento
2025	A*	`conf`	Learning Randomized Algorithms with Transformers. ICLR Johannes von Oswald, Seijin Kobayashi, Yassir Akram, Angelika Steger
2025	J	`jnl`	MesaNet: Sequence Modeling by Locally Optimal Test-Time Training. CoRR Johannes von Oswald, Nino Scherrer, Seijin Kobayashi, Luca Versari, Songlin Yang, Maximilian Schlegel, Kaitlin Maile, Yanick Schimpf, Oliver Sieberling, Alexander Meulemans, Rif A. Saurous, Guillaume Lajoie, Charlotte Frenkel, Razvan Pascanu, Blaise Agüera y Arcas, João Sacramento
2025	A*	`conf`	Multi-agent cooperation through learning-aware policy gradients. ICLR Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake Aaron Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento
2024	J	`jnl`	Attention as a Hypernetwork. CoRR Simon Schug, Seijin Kobayashi, Yassir Akram, João Sacramento, Razvan Pascanu
2024	A*	`conf`	Discovering modular solutions that generalize compositionally. ICLR Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Maria Proca, Johannes von Oswald, Razvan Pascanu, João Sacramento, Angelika Steger
2024	J	`jnl`	Learning Randomized Algorithms with Transformers. CoRR Johannes von Oswald, Seijin Kobayashi, Yassir Akram, Angelika Steger
2024	J	`jnl`	Multi-agent cooperation through learning-aware policy gradients. CoRR Alexander Meulemans, Seijin Kobayashi, Johannes von Oswald, Nino Scherrer, Eric Elmoznino, Blake A. Richards, Guillaume Lajoie, Blaise Agüera y Arcas, João Sacramento
2024	A*	`conf`	Weight decay induces low-rank attention layers. NeurIPS Seijin Kobayashi, Yassir Akram, Johannes von Oswald
2024	J	`jnl`	Weight decay induces low-rank attention layers. CoRR Seijin Kobayashi, Yassir Akram, Johannes von Oswald
2024	J	`jnl`	When can transformers compositionally generalize in-context? CoRR Seijin Kobayashi, Simon Schug, Yassir Akram, Florian Redhardt, Johannes von Oswald, Razvan Pascanu, Guillaume Lajoie, João Sacramento
2023	J	`jnl`	Discovering modular solutions that generalize compositionally. CoRR Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Maria Proca, Johannes von Oswald, Razvan Pascanu, João Sacramento, Angelika Steger
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	J	`jnl`	Meta-Learning via Classifier(-free) Diffusion Guidance. Trans. Mach. Learn. Res. Elvis Nava, Seijin Kobayashi, Yifei Yin, Robert K. Katzschmann, Benjamin F. Grewe
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
2023	A*	`conf`	Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis. NeurIPS Alexander Meulemans, Simon Schug, Seijin Kobayashi, Nathaniel D. Daw, Gregory Wayne
2023	J	`jnl`	Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis. CoRR Alexander Meulemans, Simon Schug, Seijin Kobayashi, Nathaniel D. Daw, Gregory Wayne
2022	A*	`conf`	Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel. NeurIPS Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald
2022	J	`jnl`	Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel. CoRR Seijin Kobayashi, Pau Vilimelis Aceituno, Johannes von Oswald
2022	J	`jnl`	Meta-Learning via Classifier(-free) Guidance. CoRR Elvis Nava, Seijin Kobayashi, Yifei Yin, Robert K. Katzschmann, Benjamin F. Grewe
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	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
2021	A*	`conf`	Neural networks with late-phase weights. ICLR Johannes von Oswald, Seijin Kobayashi, João Sacramento, Alexander Meulemans, Christian Henning, Benjamin F. Grewe
2021	A*	`conf`	Posterior Meta-Replay for Continual Learning. NeurIPS Christian Henning, Maria R. Cervera, Francesco D'Angelo, Johannes von Oswald, Regina Traber, Benjamin Ehret, Seijin Kobayashi, Benjamin F. Grewe, João Sacramento
2021	J	`jnl`	Posterior Meta-Replay for Continual Learning. CoRR Christian Henning, Maria R. Cervera, Francesco D'Angelo, Johannes von Oswald, Regina Traber, Benjamin Ehret, Seijin Kobayashi, João Sacramento, Benjamin F. Grewe
2020	J	`jnl`	Economical ensembles with hypernetworks. CoRR João Sacramento, Johannes von Oswald, Seijin Kobayashi, Christian Henning, Benjamin F. Grewe
2018	J	`jnl`	Wheel Defect Detection With Machine Learning. IEEE Trans. Intell. Transp. Syst. Gabriel Krummenacher, Cheng Soon Ong, Stefan Koller, Seijin Kobayashi, Joachim M. Buhmann