Samuel Kessler

According to our database, Samuel Kessler authored at least 11 papers between 2019 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

On Sequential Bayesian Inference for Continual Learning.

Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts

Entropy, June, 2023

Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies.

Kieran Wood, Samuel Kessler, Stephen J. Roberts, Stefan Zohren

CoRR, 2023

The Effectiveness of World Models for Continual Reinforcement Learning.

Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning.

Samuel Kessler, Piotr Milos, Jack Parker-Holder, Stephen J. Roberts

CoRR, 2022

Efficient Adapter Transfer of Self-Supervised Speech Models for Automatic Speech Recognition.

Bethan Thomas, Samuel Kessler, Salah Karout

Proceedings of the IEEE International Conference on Acoustics, 2022

An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation Learning.

Samuel Kessler, Bethan Thomas, Salah Karout

Proceedings of the IEEE International Conference on Acoustics, 2022

Follow the Leader: Technical and Inspirational Leadership in Open Source Software.

Jérôme Hergueux, Samuel Kessler

Proceedings of the CHI '22: CHI Conference on Human Factors in Computing Systems, New Orleans, LA, USA, 29 April 2022, 2022

Same State, Different Task: Continual Reinforcement Learning without Interference.

Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Continual-wav2vec2: an Application of Continual Learning for Self-Supervised Automatic Speech Recognition.

Samuel Kessler, Bethan Thomas, Salah Karout

CoRR, 2021

Hierarchical Indian buffet neural networks for Bayesian continual learning.

Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen J. Roberts

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2019

Indian Buffet Neural Networks for Continual Learning.

Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen Roberts

CoRR, 2019