1 citations · 1 across the 9 of their papers we have counts for
9 papers
Joinings in Markov categories
Suddhasattwa Das, Tomoharu Suda
Dynamical systems theory primarily concerns the study of different forms of invariance, such as invariant sets, densities, measures, and observables. Ergodic systems are a special…
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…
Dynamics, data and reconstruction
Suddhasattwa Das, Tomoharu Suda
The goal of data-driven learning of dynamical systems is to interpret time series as a continuous observation of an underlying dynamical system. This task is not well-posed for a v…
Discrete-time dynamics, step-skew products, and pipe-flows
Suddhasattwa Das
Dynamical processes can be classified in various ways as deterministic or stochastic, and continuous or discrete time. All these types can be studied by the path-spaces they genera…
A probabilistic approach to drift estimation from stochastic data
Suddhasattwa Das
Timeseries generated from a dynamical source can often be modeled as sample paths of a stochastic differential equation (SDE). The timeseries thus reflects the motion of a particle…
Smooth Koopman eigenfunctions
Suddhasattwa Das
Any dynamical system, whether it is generated by a differential equation or a transformation map on a manifold, induces a dynamics on functional-spaces. The choice of functional-sp…