A list of publications, broadly cathegorised in three groups: “AI/ML for Science”, “AI/ML” and “AI/ML for Econ”. An up-to-date list of publications is also available on my Google Scholar page .
2025 AI/ML for Econ
BeforeIT.jl: High-Performance Agent-Based Macroeconomics Made Easy
Aldo Glielmo , Mitja Devetak, Adriano Meligrana, and 1 more author
arXiv preprint arXiv:2502.13267 , 2025
Assessing inference to the best explanation posteriors for the estimation of economic agent-based models
Francesco De Pretis, Aldo Glielmo , and Jürgen Landes
International Journal of Approximate Reasoning , 2025
AI/ML for Econ
Agent-based modeling at central banks: Recent developments and new challenges
András Borsos, Adrian Carro, Aldo Glielmo , and 3 more authors
Bank of England Staff Working Paper , 2025
AI/ML for Econ
Robust Policy Design in Agent-Based Simulators using Adversarial Reinforcement Learning
Akash Agrawal, Joel Dyer, Aldo Glielmo , and 1 more author
In The First MARW: Multi-Agent AI in the Real World Workshop at AAAI 2025 , 2025
2024 Divide-and-conquer potentials enable scalable and accurate predictions of forces and energies in atomistic systems
Claudio Zeni, Andrea Anelli, Aldo Glielmo , and 2 more authors
Digital Discovery , 2024
AI/ML for Econ
Simulating the Economic Impact of Rationality through Reinforcement Learning and Agent-Based Modelling
Simone Brusatin, Tommaso Padoan, Andrea Coletta, and 2 more authors
In Proceedings of the 5th ACM International Conference on AI in Finance , 2024
AI/ML
Beyond the noise: intrinsic dimension estimation with optimal neighbourhood identification
Antonio Di Noia, Iuri Macocco, Aldo Glielmo , and 2 more authors
arXiv preprint arXiv:2405.15132 , 2024
AI/ML for Econ
Investigating the price determinants of the European Emission Trading System: a non-parametric approach
Cristiano Salvagnin, Aldo Glielmo , Maria Elena De Giuli, and 1 more author
Quantitative Finance , 2024
AI/ML
Density Estimation via Binless Multidimensional Integration
Matteo Carli, Alex Rodriguez, Alessandro Laio, and 1 more author
Machine Learning Science and Technology (accepted) , 2024
AI/ML
Understanding Variational Autoencoders with Intrinsic Dimension and Information Imbalance
Charles Camboulin, Diego Doimo, and Aldo Glielmo
In UniReps: 2nd Edition of the Workshop on Unifying Representations in Neural Models , 2024
AI/ML for Econ
Chat Bankman-Fried? an Exploration of LLM Alignment in Finance
Claudia Biancotti, Carolina Camassa, Andrea Coletta, and 2 more authors
Available at SSRN 5005794 , 2024
Unveiling the Mechanisms of DAI: A Logic-Based Approach to Stablecoin Analysis
Francesco De Sclavis, Giuseppe Galano, Aldo Glielmo , and 1 more author
arXiv preprint arXiv:2412.15814 , 2024
2023 Reconstruction and segmentation from sparse sequential X-ray measurements of wood logs
Sebastian Springer, Aldo Glielmo , Angelina Senchukova, and 5 more authors
Applied Mathematics for Modern Challenges , 2023
AI/ML
Intrinsic dimension estimation for discrete metrics
Iuri Macocco, Aldo Glielmo , Jacopo Grilli, and 1 more author
Physical Review Letters , 2023
AI/ML for Econ
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs
Aldo Glielmo , Marco Favorito, Debmallya Chanda, and 1 more author
In Proceedings of the Fourth ACM International Conference on AI in Finance , 2023
Redundant representations help generalization in wide neural networks
Diego Doimo, Aldo Glielmo , Sebastian Goldt, and 1 more author
Journal of Statistical Mechanics: Theory and Experiment , 2023
2022 AI/ML
Ranking the information content of distance measures
Aldo Glielmo , Claudio Zeni, Bingqing Cheng, and 2 more authors
PNAS Nexus , 2022
Exploring the robust extrapolation of high-dimensional machine learning potentials
Claudio Zeni, Andrea Anelli, Aldo Glielmo , and 1 more author
Physical Review B , 2022
AI/ML
DADApy: Distance-based analysis of data-manifolds in Python
Aldo Glielmo , Iuri Macocco, Diego Doimo, and 6 more authors
Patterns , 2022
AI/ML for Econ
Black-it: A ready-to-use and easy-to-extend calibration kit for agent-based models
Marco Benedetti, Gennaro Catapano, Francesco De Sclavis, and 4 more authors
Journal of Open Source Software , 2022
AI/ML
Redundant representations help generalization in wide neural networks
Diego Doimo, Aldo Glielmo , Sebastian Goldt, and 1 more author
Advances in Neural Information Processing Systems , 2022
2021 Unsupervised learning methods for molecular simulation data
Aldo Glielmo , Brooke E Husic, Alex Rodriguez, and 3 more authors
Chemical Reviews , 2021
Compact atomic descriptors enable accurate predictions via linear models
Claudio Zeni, Kevin Rossi, Aldo Glielmo , and 1 more author
The Journal of Chemical Physics , 2021
2020 Building nonparametric n-body force fields using gaussian process regression
Aldo Glielmo , Claudio Zeni, Adám Fekete, and 1 more author
Machine Learning Meets Quantum Physics , 2020
AI/ML for Science
Gaussian Process States: A data-driven representation of quantum many-body physics
Aldo Glielmo , Yannic Rath, Gabor Csanyi, and 2 more authors
Physical Review X , 2020
AI/ML
Hierarchical nucleation in deep neural networks
Diego Doimo, Aldo Glielmo , Alessandro Laio, and 1 more author
In Advances in Neural Information Processing Systems 33 (NeurIPS 2020) , 2020
A Bayesian inference framework for compression and prediction of quantum states
Yannic Rath, Aldo Glielmo , and George H Booth
The Journal of chemical physics , 2020
2019 Stochastic nature of particle collisions and its impact on granular material properties
Nina Gunkelmann, Dan Serero, Aldo Glielmo , and 3 more authors
Particles in Contact: Micro Mechanics, Micro Process Dynamics and Particle Collective , 2019
Enabling QM-accurate simulation of dislocation motion in γ-Ni and α-Fe using a hybrid multiscale approach
Federico Bianchini, Aldo Glielmo , James R Kermode, and 1 more author
Physical Review Materials , 2019
AI/ML
SPONGE: A generalized eigenproblem for clustering signed networks
Mihai Cucuringu, Peter Davies, Aldo Glielmo , and 1 more author
In Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics , 16–18 apr 2019
On machine learning force fields for metallic nanoparticles
Claudio Zeni, Kevin Rossi, Aldo Glielmo , and 1 more author
Advances in Physics: X , 16–18 apr 2019
Gaussian processes for force fields and wave functions
Aldo Glielmo
King’s College London , 16–18 apr 2019
This thesis was awarded the Institute of Physics computational thesis prize and the Elsevier outstanding PhD thess prize.
2018 Building machine learning force fields for nanoclusters
Claudio Zeni, Kevin Rossi, Aldo Glielmo , and 4 more authors
The Journal of chemical physics , 16–18 apr 2018
Efficient nonparametric n-body force fields from machine learning
Aldo Glielmo , Claudio Zeni, and Alessandro De Vita
Physical Review B , 16–18 apr 2018
2017 Accurate interatomic force fields via machine learning with covariant kernels
Aldo Glielmo , Peter Sollich, and Alessandro De Vita
Physical Review B , 16–18 apr 2017
2016 Can we obtain the coefficient of restitution from the sound of a bouncing ball?
Michael Heckel, Aldo Glielmo , Nina Gunkelmann, and 1 more author
Physical Review E , 16–18 apr 2016
2014 Coefficient of restitution of aspherical particles
Aldo Glielmo , Nina Gunkelmann, and Thorsten Pöschel
Physical Review E , 16–18 apr 2014
Agent-based modeling at central banks: Recent developments and new challengesBank of England Staff Working Paper, 2025
Beyond the noise: intrinsic dimension estimation with optimal neighbourhood identificationarXiv preprint arXiv:2405.15132, 2024
Gaussian Process States: A data-driven representation of quantum many-body physicsPhysical Review X, 2020
