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Nicola Paoletti

11 papers hereh-index 323 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author1
  • last author8

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.AI3
  • cs.CE1
  • cs.LO1
  • cs.MA1
  • eess.SY1
same name
  • Nicola Paoletti — 19 papers, h 21
  • Nicola Paoletti — 6 papers, h 4
  • Nicola Paoletti — 6 papers, h 4
  • Nicola Paoletti — 6 papers, h 1
  • Nicola Paoletti — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182026
most citedConformal Off-Policy Prediction for Multi-Agent Systems

3 citations · 6 across the 8 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

Robust Counterfactual Policy Optimisation via Nondeterministic Causal Models

Jessica Lally, Milad Kazemi, Nicola Paoletti +2

Counterfactual inference approaches for sequential decision-making typically assume deterministic causal models, where all randomness stems from latent variables. However, Markov D…

cs.LG2025

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…

cs.LG2025

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…

cs.LG2025

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…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.