Johannes von Oswald

According to our database¹, Johannes von Oswald authored at least 21 papers between 2020 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

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In proceedings

Article

PhD thesis

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On csauthors.net:

Bibliography

2024

Interpretability of Learning Algorithms Encoded in Deep Neural Networks.

[BibT_eX]

[DOI]

Johannes von Oswald

PhD thesis, 2024

Learning Randomized Algorithms with Transformers.

[BibT_eX]

[DOI]

CoRR, 2024

When can transformers compositionally generalize in-context?

[BibT_eX]

[DOI]

CoRR, 2024

State Soup: In-Context Skill Learning, Retrieval and Mixing.

[BibT_eX]

[DOI]

CoRR, 2024

Linear Transformers are Versatile In-Context Learners.

[BibT_eX]

[DOI]

CoRR, 2024

Discovering modular solutions that generalize compositionally.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Uncovering mesa-optimization algorithms in Transformers.

[BibT_eX]

[DOI]

Blaise Agüera y Arcas

Max Vladymyrov

Razvan Pascanu

João Sacramento

CoRR, 2023

Gated recurrent neural networks discover attention.

[BibT_eX]

[DOI]

CoRR, 2023

Transformers Learn In-Context by Gradient Descent.

[BibT_eX]

[DOI]

Alexander Mordvintsev

Andrey Zhmoginov

Max Vladymyrov

Proceedings of the International Conference on Machine Learning, 2023

2022

Random initialisations performing above chance and how to find them.

[BibT_eX]

[DOI]

CoRR, 2022

The least-control principle for learning at equilibrium.

[BibT_eX]

[DOI]

CoRR, 2022

A contrastive rule for meta-learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The least-control principle for local learning at equilibrium.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel.

[BibT_eX]

[DOI]

Seijin Kobayashi

Pau Vilimelis Aceituno

Johannes von Oswald

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Learning where to learn: Gradient sparsity in meta and continual learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Posterior Meta-Replay for Continual Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural networks with late-phase weights.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Continual learning in recurrent neural networks.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Economical ensembles with hypernetworks.

[BibT_eX]

[DOI]

CoRR, 2020

Continual Learning in Recurrent Neural Networks with Hypernetworks.

[BibT_eX]

[DOI]

CoRR, 2020

Continual learning with hypernetworks.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Johannes von Oswald

Timeline

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