no code implementations • 3 Aug 2023 • Asen Nachkov, Luchen Li, Giulia Luise, Filippo Valdettaro, Aldo Faisal
To test whether optimistic ensemble method can improve on distributional RL as did on scalar RL, by e. g. Bootstrapped DQN, we implement the BoP approach with a population of distributional actor-critics using Bayesian Distributional Policy Gradients (BDPG).
no code implementations • 23 Jun 2022 • Benjamin Post, Cosmin Badea, Aldo Faisal, Stephen J. Brett
An appropriate ethical framework around the use of Artificial Intelligence (AI) in healthcare has become a key desirable with the increasingly widespread deployment of this technology.
no code implementations • 10 Mar 2021 • Denghao Li, Pablo Ortega, Xiaoxi Wei, Aldo Faisal
We introduce here the idea of Meta-Learning for training EEG BCI decoders.
no code implementations • 9 Mar 2021 • Pablo Ortega, Aldo Faisal
We solve the fNIRS left/right hand force decoding problem using a data-driven approach by using a convolutional neural network architecture, the HemCNN.
no code implementations • 9 Mar 2021 • Pablo Ortega, Tong Zhao, Aldo Faisal
Non-invasive cortical neural interfaces have only achieved modest performance in cortical decoding of limb movements and their forces, compared to invasive brain-computer interfaces (BCIs).
1 code implementation • 29 Jul 2019 • Robert Tjarko Lange, Aldo Faisal
By treating an on-policy trajectory as a sentence sampled from the policy-conditioned language of the environment, we identify hierarchical constituents with the help of unsupervised grammatical inference.
no code implementations • 7 Mar 2019 • Ekaterina Abramova, Luke Dickens, Daniel Kuhn, Aldo Faisal
We show that a small number of locally optimal linear controllers are able to solve global nonlinear control problems with unknown dynamics when combined with a reinforcement learner in this hierarchical framework.
no code implementations • 15 Jan 2019 • Xuefeng Peng, Yi Ding, David Wihl, Omer Gottesman, Matthieu Komorowski, Li-wei H. Lehman, Andrew Ross, Aldo Faisal, Finale Doshi-Velez
On a large retrospective cohort, this mixture-based approach outperforms physician, kernel only, and DRL-only experts.
no code implementations • 3 Jul 2018 • Aniruddh Raghu, Omer Gottesman, Yao Liu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
In this work, we consider the problem of estimating a behaviour policy for use in Off-Policy Policy Evaluation (OPE) when the true behaviour policy is unknown.
no code implementations • 31 May 2018 • Omer Gottesman, Fredrik Johansson, Joshua Meier, Jack Dent, Dong-hun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David Sontag, Finale Doshi-Velez
Much attention has been devoted recently to the development of machine learning algorithms with the goal of improving treatment policies in healthcare.
1 code implementation • NeurIPS 2018 • Yao Liu, Omer Gottesman, Aniruddh Raghu, Matthieu Komorowski, Aldo Faisal, Finale Doshi-Velez, Emma Brunskill
We study the problem of off-policy policy evaluation (OPPE) in RL.