8 citations · 17 across the 13 of their papers we have counts for
6 papers · 1 filter
Physics-Informed Neural Operators for Cardiac Electrophysiology
Hannah Lydon, Milad Kazemi, Martin Bishop +1
Accurately simulating systems governed by PDEs, such as voltage fields in cardiac electrophysiology (EP) modelling, remains a significant modelling challenge. Traditional numerical…
CONFEX: Uncertainty-Aware Counterfactual Explanations with Conformal Guarantees
Aman Bilkhoo, Mehran Hosseini, Milad Kazemi +1
Counterfactual explanations (CFXs) provide human-understandable justifications for model predictions, enabling actionable recourse and enhancing interpretability. To be reliable, C…
Abstract Counterfactuals for Language Model Agents
Edoardo Pona, Milad Kazemi, Yali Du +2
Counterfactual inference is a powerful tool for analysing and evaluating autonomous agents, but its application to language model (LM) agents remains challenging. Existing work on…
SimICD: A Closed-Loop Simulation Framework For ICD Therapy
Hannah Lydon, Milad Kazemi, Martin Bishop +1
Virtual studies of ICD behaviour are crucial for testing device functionality in a controlled environment prior to clinical application. Although previous works have shown the viab…
Average Reward Reinforcement Learning for Omega-Regular and Mean-Payoff Objectives
Milad Kazemi, Mateo Perez, Fabio Somenzi +3
Recent advances in reinforcement learning (RL) have renewed interest in reward design for shaping agent behavior, but manually crafting reward functions is tedious and error-prone.…
Robust Counterfactual Inference in Markov Decision Processes
Jessica Lally, Milad Kazemi, Nicola Paoletti
This paper addresses a key limitation in existing counterfactual inference methods for Markov Decision Processes (MDPs). Current approaches assume a specific causal model to make c…