Sebastian Macaluso

According to our database, Sebastian Macaluso authored at least 9 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Quantum Computing for Large-scale Network Optimization: Opportunities and Challenges.

Sebastian Macaluso, Giovanni Geraci, Elías F. Combarro, Sergi Abadal, Ioannis Arapakis, Sofia Vallecorsa, Eduard Alarcón

CoRR, September, 2025

Mind the XAI Gap: A Human-Centered LLM Framework for Democratizing Explainable AI.

Eva Paraschou, Ioannis Arapakis, Sofia Yfantidou, Sebastian Macaluso, Athena Vakali

CoRR, June, 2025

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

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, Rosaria Rossini, Sofia Tsekeridou, Dimitrios Tsoukalas, Christina Volioti, Apostolos Vontas, Vassilis Voulgarakis

Proceedings of the 50th Euromicro Conference on Software Engineering and Advanced Applications, 2024

2021

The Quantum Trellis: A classical algorithm for sampling the parton shower with interference effects.

Sebastian Macaluso, Kyle Cranmer

CoRR, 2021

Exact and approximate hierarchical clustering using A.

Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

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, Andrew McCallum

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Hierarchical clustering in particle physics through reinforcement learning.

Johann Brehmer, Sebastian Macaluso, Duccio Pappadopulo, Kyle Cranmer

CoRR, 2020

Compact Representation of Uncertainty in Hierarchical Clustering.

Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Ji Ah Lee, Patrick Flaherty, Kyle Cranmer, Andrew McGregor, Andrew McCallum

CoRR, 2020