6 papers
NestyNet. III. Symbolic Regression from Analytic Neural Surrogates
Rodrigo Ibata, Wassim Tenachi, Foivos Diakogiannis +2
Many physical laws are simple only after the right representation, decomposition or internal coordinate has been found, but discovering that structure from data is combinatorially…
NestyNet. II. Coherent Function-Space Posteriors from Scientific Neural Surrogates (or How to Avoid Expensive MCMC)
Rodrigo Ibata, Wassim Tenachi, Foivos Diakogiannis +2
Scientific analyses increasingly use flexible neural networks, but their thousands of correlated parameters make it challenging to interpret the associated uncertainties. Here we d…
NestyNet. I. Physics Functions Are Hard to Fit with Neural Networks: A Framework for Accurate Surrogates and Analytic Derivatives
Rodrigo Ibata, Wassim Tenachi, Foivos Diakogiannis +2
Many of the smooth functions that matter most in physics are precisely the ones that standard neural network methods struggle to fit accurately. Here we present NestyNet, a coupled…
Conditional Image Diffusion with Interferometric Closure Invariants: Independent EHT Imaging of Centaurus~A and 3C~279
Samuel Lai, Nithyanandan Thyagarajan, O. Ivy Wong +1
We present independent imaging analyses of Event Horizon Telescope (EHT) observations of the active galactic nuclei in radio galaxy Centaurus~A and quasar 3C~279 using Generative D…
Very-Long Baseline Interferometry Imaging with Closure Invariants using Conditional Image Diffusion
Samuel Lai, Nithyanandan Thyagarajan, O. Ivy Wong +1
Image reconstruction in very-long baseline interferometry operates under severely sparse aperture coverage with calibration challenges from both the participating instruments and p…
Tackling fluffy clouds: robust field boundary delineation across global agricultural landscapes with Sentinel-1 and Sentinel-2 Time Series
Foivos I. Diakogiannis, Zheng-Shu Zhou, Jeff Wang +12
Accurate delineation of agricultural field boundaries is essential for effective crop monitoring and resource management. However, competing methodologies often face significant ch…