4 papers
Physics-informed machine learning for reconstruction of dynamical systems with invariant measure score matching
Yongsheng Chen, Suddhasattwa Das, Wei Guo +1
In this paper, we develop a novel mesh-free framework, termed physics-informed neural networks with invariant measure score matching (PINN-IMSM), for reconstructing dynamical syste…
Dynamical systems as enriched functors
Suddhasattwa Das, Tomoharu Suda
This article presents a general description of dynamical systems using the language of enriched functors and enriched natural transformations. This framework is essential to establ…
The concept of null in general spaces and contexts
Suddhasattwa Das
The notions of null-sets and nullity are present in all discourses of mathematics. They are based on the dual-pair of notions of "almost-every" and "almost none". A notion of nulli…
Image denoising as a conditional expectation
Sajal Chakroborty, Suddhasattwa Das
All techniques for denoising involve a notion of a true (noise-free) image, and a hypothesis space. The hypothesis space may reconstruct the image directly as a grayscale valued fu…