57 citations · 82 across the 13 of their papers we have counts for
3 papers · 1 filter
Self-Tuning Hamiltonian Monte Carlo for Accelerated Sampling
Henrik Christiansen, Federico Errica, Francesco Alesiani
The performance of Hamiltonian Monte Carlo simulations crucially depends on both the integration timestep and the number of integration steps. We present an adaptive general-purpos…
Learning Neural PDE Solvers with Parameter-Guided Channel Attention
Makoto Takamoto, Francesco Alesiani, Mathias Niepert
Scientific Machine Learning (SciML) is concerned with the development of learned emulators of physical systems governed by partial differential equations (PDE). In application doma…
Implicit Bilevel Optimization: Differentiating through Bilevel Optimization Programming
Francesco Alesiani
Bilevel Optimization Programming is used to model complex and conflicting interactions between agents, for example in Robust AI or Privacy-preserving AI. Integrating bilevel mathem…