Compact Representation of Uncertainty in Hierarchical Clustering. - Craig S. Greenberg; Sebastian Macaluso; Nicholas Monath; Ji Ah Lee; Patrick Flaherty; Kyle Cranmer; Andrew McGregor 001; Andrew McCallum (CoRR, 2020)

Hierarchical clustering in particle physics through reinforcement learning. - Johann Brehmer; Sebastian Macaluso; Duccio Pappadopulo; Kyle Cranmer (CoRR, 2020)

Cluster Trellis: Data Structures & Algorithms for Exact Inference in Hierarchical Clustering. - Sebastian Macaluso; Craig S. Greenberg; Nicholas Monath; Ji Ah Lee; Patrick Flaherty; Kyle Cranmer; Andrew McGregor 001; Andrew McCallum (AISTATS, 2021)

Exact and approximate hierarchical clustering using A. - Craig S. Greenberg; Sebastian Macaluso; Nicholas Monath; Avinava Dubey; Patrick Flaherty; Manzil Zaheer; Amr Ahmed 001; Kyle Cranmer; Andrew McCallum (UAI, 2021)

The Quantum Trellis: A classical algorithm for sampling the parton shower with interference effects. - Sebastian Macaluso; Kyle Cranmer (CoRR, 2021)

SKILLAB: Skills Matter. - Mihaela Aluas; Lefteris Angelis; Ioannis Arapakis; Elvira-Maria Arvanitou; Kostantinos Georgiou; Anastasios Gogos; Marco Jahn; Dionysios D. Kehagias; Valia Kordoni; Sebastian Macaluso; Nikolaos Mittas; Vasiliki Moumtzi; et al. (SEAA, 2024)

Variational Pseudo Marginal Methods for Jet Reconstruction in Particle Physics. - Hanming Yang; Antonio Khalil Moretti; Sebastian Macaluso; Philippe Chlenski; Christian A. Naesseth; Itsik Pe'er (Trans. Mach. Learn. Res., 2024)

Mind the XAI Gap: A Human-Centered LLM Framework for Democratizing Explainable AI. - Eva Paraschou; Ioannis Arapakis; Sofia Yfantidou; Sebastian Macaluso; Athena Vakali (CoRR, 2025)