14 citations · 30 across the 8 of their papers we have counts for
14 papers
Transform Once: Efficient Operator Learning in Frequency Domain
Michael Poli, Stefano Massaroli, Federico Berto +4
Spectral analysis provides one of the most effective paradigms for information-preserving dimensionality reduction, as simple descriptions of naturally occurring signals are often…
Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations
Michael Poli, Winnie Xu, Stefano Massaroli +3
Many patterns in nature exhibit self-similarity: they can be compactly described via self-referential transformations. Said patterns commonly appear in natural and artificial objec…
Neural Solvers for Fast and Accurate Numerical Optimal Control
Federico Berto, Stefano Massaroli, Michael Poli +1
Synthesizing optimal controllers for dynamical systems often involves solving optimization problems with hard real-time constraints. These constraints determine the class of numeri…
Continuous-Depth Neural Models for Dynamic Graph Prediction
Michael Poli, Stefano Massaroli, Clayton M. Rabideau +4
We introduce the framework of continuous-depth graph neural networks (GNNs). Neural graph differential equations (Neural GDEs) are formalized as the counterpart to GNNs where the i…
Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions
Michael Poli, Stefano Massaroli, Luca Scimeca +6
Effective control and prediction of dynamical systems often require appropriate handling of continuous-time and discrete, event-triggered processes. Stochastic hybrid systems (SHSs…
Differentiable Multiple Shooting Layers
Stefano Massaroli, Michael Poli, Sho Sonoda +4
We detail a novel class of implicit neural models. Leveraging time-parallel methods for differential equations, Multiple Shooting Layers (MSLs) seek solutions of initial value prob…