Comparing recurrent and convolutional neural networks for predicting wave propagation. - Stathi Fotiadis; Eduardo Pignatelli; Mario Lino Valencia; Chris D. Cantwell; Amos J. Storkey; Anil A. Bharath (CoRR, 2020)

Simulating Surface Wave Dynamics with Convolutional Networks. - Mario Lino Valencia; Chris D. Cantwell; Stathi Fotiadis; Eduardo Pignatelli; Anil A. Bharath (CoRR, 2020)

Estimating Cardiac Tissue Conductivity from Electrograms with Fully Convolutional Networks. - Konstantinos Ntagiantas; Eduardo Pignatelli; Nicholas S. Peters; Chris D. Cantwell; Rasheda A. Chowdhury; Anil A. Bharath (CoRR, 2022)

Estimation of fibre architecture and scar in myocardial tissue using electrograms: An in-silico study. - Konstantinos Ntagiantas; Eduardo Pignatelli; Nicholas S. Peters; Chris D. Cantwell; Rasheda A. Chowdhury; Anil A. Bharath (Biomed. Signal Process. Control., 2024)

NAVIX: Scaling MiniGrid Environments with JAX. - Eduardo Pignatelli; Jarek Liesen; Robert Tjarko Lange; Chris Lu 001; Pablo Samuel Castro; Laura Toni (CoRR, 2024)

Assessing the Zero-Shot Capabilities of LLMs for Action Evaluation in RL. - Eduardo Pignatelli; Johan Ferret; Tim Rocktäschel; Edward Grefenstette; Davide Paglieri; Samuel Coward; Laura Toni (CoRR, 2024)

A Survey of Temporal Credit Assignment in Deep Reinforcement Learning. - Eduardo Pignatelli; Johan Ferret; Matthieu Geist; Thomas Mesnard; Hado van Hasselt; Laura Toni (Trans. Mach. Learn. Res., 2024)

BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games. - Davide Paglieri; Bartlomiej Cupial; Samuel Coward; Ulyana Piterbarg; Maciej Wolczyk; Akbir Khan; Eduardo Pignatelli; Lukasz Kucinski; Lerrel Pinto; Rob Fergus; Jakob Nicolaus Foerster; Jack Parker-Holder; et al. (ICLR, 2025)

The impact of intrinsic rewards on exploration in Reinforcement Learning. - Aya Kayal; Eduardo Pignatelli; Laura Toni (Neural Comput. Appl., 2025)