Diana Borsa

According to our database, Diana Borsa authored at least 25 papers between 2015 and 2024.

Collaborative distances:

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

2024

A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning.

Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Ávila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana Borsa, Arthur Guez, Will Dabney

CoRR, 2024

2023

A State Representation for Diminishing Rewards.

Ted Moskovitz, Samo Hromadka, Ahmed Touati, Diana Borsa, Maneesh Sahani

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition.

Yash Chandak, Shantanu Thakoor, Zhaohan Daniel Guo, Yunhao Tang, Rémi Munos, Will Dabney, Diana L. Borsa

Proceedings of the International Conference on Machine Learning, 2023

2022

Selective Credit Assignment.

Veronica Chelu, Diana Borsa, Doina Precup, Hado van Hasselt

CoRR, 2022

Generalised Policy Improvement with Geometric Policy Composition.

Shantanu Thakoor, Mark Rowland, Diana Borsa, Will Dabney, Rémi Munos, André Barreto

Proceedings of the International Conference on Machine Learning, 2022

Model-Value Inconsistency as a Signal for Epistemic Uncertainty.

Angelos Filos, Eszter Vértes, Zita Marinho, Gregory Farquhar, Diana Borsa, Abram L. Friesen, Feryal M. P. Behbahani, Tom Schaul, André Barreto, Simon Osindero

Proceedings of the International Conference on Machine Learning, 2022

When should agents explore?

Miruna Pislar, David Szepesvari, Georg Ostrovski, Diana L. Borsa, Tom Schaul

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Return-based Scaling: Yet Another Normalisation Trick for Deep RL.

Tom Schaul, Georg Ostrovski, Iurii Kemaev, Diana Borsa

CoRR, 2021

Expected Eligibility Traces.

Hado van Hasselt, Sephora Madjiheurem, Matteo Hessel, David Silver, André Barreto, Diana Borsa

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Reinforcement learning in persistent environments: representation learning and transfer.

Diana Borsa

PhD thesis, 2020

Fast reinforcement learning with generalized policy updates.

André Barreto, Shaobo Hou, Diana Borsa, David Silver, Doina Precup

Proc. Natl. Acad. Sci. USA, 2020

Temporal Difference Uncertainties as a Signal for Exploration.

Sebastian Flennerhag, Jane X. Wang, Pablo Sprechmann, Francesco Visin, Alexandre Galashov, Steven Kapturowski, Diana L. Borsa, Nicolas Heess, André Barreto, Razvan Pascanu

CoRR, 2020

Conditional Importance Sampling for Off-Policy Learning.

Mark Rowland, Anna Harutyunyan, Hado van Hasselt, Diana Borsa, Tom Schaul, Rémi Munos, Will Dabney

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Adapting Behaviour for Learning Progress.

Tom Schaul, Diana Borsa, David Ding, David Szepesvari, Georg Ostrovski, Will Dabney, Simon Osindero

CoRR, 2019

General non-linear Bellman equations.

Hado van Hasselt, John Quan, Matteo Hessel, Zhongwen Xu, Diana Borsa, André Barreto

CoRR, 2019

Ray Interference: a Source of Plateaus in Deep Reinforcement Learning.

Tom Schaul, Diana Borsa, Joseph Modayil, Razvan Pascanu

CoRR, 2019

The Option Keyboard: Combining Skills in Reinforcement Learning.

André Barreto, Diana Borsa, Shaobo Hou, Gheorghe Comanici, Eser Aygün, Philippe Hamel, Daniel Toyama, Jonathan J. Hunt, Shibl Mourad, David Silver, Doina Precup

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Universal Successor Features Approximators.

Diana Borsa, André Barreto, John Quan, Daniel J. Mankowitz, Hado van Hasselt, Rémi Munos, David Silver, Tom Schaul

Proceedings of the 7th International Conference on Learning Representations, 2019

Observational Learning by Reinforcement Learning.

Diana Borsa, Nicolas Heess, Bilal Piot, Siqi Liu, Leonard Hasenclever, Rémi Munos, Olivier Pietquin

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

The Termination Critic.

Anna Harutyunyan, Will Dabney, Diana Borsa, Nicolas Heess, Rémi Munos, Doina Precup

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Transfer in Deep Reinforcement Learning Using Successor Features and Generalised Policy Improvement.

André Barreto, Diana Borsa, John Quan, Tom Schaul, David Silver, Matteo Hessel, Daniel J. Mankowitz, Augustin Zídek, Rémi Munos

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Observational Learning by Reinforcement Learning.

Diana Borsa, Bilal Piot, Rémi Munos, Olivier Pietquin

CoRR, 2017

2016

Learning Shared Representations in Multi-task Reinforcement Learning.

Diana Borsa, Thore Graepel, John Shawe-Taylor

CoRR, 2016

Training Neural Nets to Aggregate Crowdsourced Responses.

Alex Gaunt, Diana Borsa, Yoram Bachrach

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016

2015

The Wreath Process: A totally generative model of geometric shape based on nested symmetries.

Diana Borsa, Thore Graepel, Andrew D. Gordon

CoRR, 2015