5 papers
Poisson-GENERIC Neural Operators: Exact Metriplectic Structure in Function Space via Casimir Entropies
Jason Sulskis, Sathya Ravi
Existing thermodynamically consistent neural operators enforce GENERIC degeneracy by projecting the reversible operator, introducing state dependence without guaranteeing Jacobi. W…
Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment
Jason Sulskis, Sathya Ravi
Fourier Neural Operators (FNO) learn solution operators of partial differential equations by parameterizing global convolutions in the complex Fourier domain. For real-valued PDE s…
GENERIC-FNO: Embedding Energy Conservation and Entropy Production into Fourier Neural Operators
Jason Sulskis, Sathya Ravi
We propose GENERIC-FNO, a neural operator that embeds the metriplectic (GENERIC) degeneracy structure of nonequilibrium thermodynamics in function space, coupling reversible, energ…
Automated RF Phase Adjustment for Beam Stabilization in the Fermilab Linac
R. R. Chichili, J. A. Sulskis, R. Sharankova +2
The Fermilab Linac experiences longitudinal beam phase drift, leading to increased particle loss, conventionally corrected through labor-intensive manual RF adjustments. This proje…
Estimating Causal Effects in Networks with Cluster-Based Bandits
Ahmed Sayeed Faruk, Jason Sulskis, Elena Zheleva
The gold standard for estimating causal effects is randomized controlled trial (RCT) or A/B testing where a random group of individuals from a population of interest are given trea…