Variational methods for Reinforcement Learning. - Thomas Furmston; David Barber (AISTATS, 2010)

Lagrange Dual Decomposition for Finite Horizon Markov Decision Processes. - Thomas Furmston; David Barber (ECML/PKDD (1), 2011)

Efficient Inference in Markov Control Problems. - Thomas Furmston; David Barber (UAI, 2011)

A Unifying Perspective of Parametric Policy Search Methods for Markov Decision Processes. - Thomas Furmston; David Barber (NIPS, 2012)

Applications of probabilistic inference to planning & reinforcement learning. - Thomas Furmston (2013)

A Gauss-Newton Method for Markov Decision Processes. - Thomas Furmston; Guy Lever (CoRR, 2015)

Approximate Newton Methods for Policy Search in Markov Decision Processes. - Thomas Furmston; Guy Lever; David Barber (J. Mach. Learn. Res., 2016)

Named Entity Recognition and Relation Extraction for COVID-19: Explainable Active Learning with Word2vec Embeddings and Transformer-Based BERT Models. - Mercedes Argüello Casteleiro; Nava Maroto; Chris Wroe; Carlos Sevillano Torrado; Chloe Henson; Jose Julio Des Diz; Maria Jesus Fernandez Prieto; Thomas Furmston; Diego Maseda-Fernandez; Manoj Kulshrestha; Robert Stevens 001; John A. Keane; et al. (SGAI Conf., 2021)