GeoLoRA: Geometric integration for parameter efficient fine-tuning

Steffen Schotthöfer, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco, Jonas Kusch
preprint, (2022)
arxiv

Low-Rank Adversarial PGD Attack

Dayana Savostianova, Emanuele Zangrando, Francesco Tudisco
preprint, (2024)
arxiv

Geometry-aware training of factorized layers in tensor Tucker format

Emanuele Zangrando, Steffen Schotthöfer, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco
Advances in Neural Information Processing Systems (NeurIPS), (2024)
arxiv

Subhomogeneous Deep Equilibrium Models

Pietro Sittoni, Francesco Tudisco
In: International Conference on Machine Learning (ICML), (2024)
arxiv doi code

Solaris: A Foundation Model for the Sun

Harris Abdul Majid, Pietro Sittoni, Francesco Tudisco
In: Advances in Neural Information Processing Systems (NeurIPS) Workshop on Foundation Models for Science, (2024)

Mixture of Neural Operators: Incorporating Historical Information for Longer Rollouts

Harris Abdul Majid, Francesco Tudisco
In: International Conference on Learning Representations (ICLR) Workshop on AI4DifferentialEquations In Science, (2024)
doi

Neural rank collapse: Weight decay and small within-class variability yield low-rank bias

Emanuele Zangrando, Piero Deidda, Simone Brugiapaglia, Nicola Guglielmi, Francesco Tudisco
preprint, (2024)
arxiv

Learning the effective order of a hypergraph dynamical system

Leonie Neuhäuser, Michael Scholkemper, Francesco Tudisco, Michael T. Schaub
Science Advances, (2024)
arxiv doi code

Robust low-rank training via approximate orthonormal constraints

Dayana Savostianova, Emanuele Zangrando, Gianluca Ceruti, Francesco Tudisco
Advances in Neural Information Processing Systems (NeurIPS), (2023)
arxiv doi code

Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations

Steffen Schotthöfer, Emanuele Zangrando, Jonas Kusch, Gianluca Ceruti, Francesco Tudisco
Advances in Neural Information Processing Systems (NeurIPS), (2022)
arxiv doi code

Learning the right layers: a data-driven layer-aggregation strategy for semi-supervised learning on multilayer graphs

Sara Venturini, Andrea Cristofari, Francesco Rinaldi, Francesco Tudisco
In: International Conference on Machine Learning (ICML), (2023)
arxiv doi code

Contractivity of neural ODEs: an eigenvalue optimization problem

Nicola Guglielmi, Arturo De Marinis, Anton Savostianov, Francesco Tudisco
Mathematics of Computation (In press), (2024)
arxiv