Marco Pacini
PhD Student at University of Trento & Fondazione Bruno Kessler
My research is focused on the theoretical aspects of Geometric Deep Learning and Equivariant Machine Learning. I received both my BSc and MSc in mathematics from the University of Pisa, specializing in Geometry and Topology.
News
| Jun 14, 2024 | New preprint of “Separation Power of Equivariant Neural Networks” is out on ArXiv now! 🎉 |
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| Jan 15, 2024 | Our latest paper “A Characterization Theorem for Equivariant Networks with Point-wise Activations” has been accepted at ICLR 2024! 📘 |
