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Found 5 papers, 2 papers with code
LoDIP: Low light phase retrieval with deep image prior
Phase retrieval (PR) is a fundamental challenge in scientific imaging, enabling nanoscale techniques like coherent diffractive imaging (CDI).
Applications of ML-Based Surrogates in Bayesian Approaches to Inverse Problems
One particular area of scientific interest is the setting of inverse problems, where one knows the forward dynamics of a system are described by a partial differential equation and the task is to infer properties of the system given (potentially noisy) observations of these dynamics.
Applications of No-Collision Transportation Maps in Manifold Learning
In this work, we investigate applications of no-collision transportation maps introduced in [Nurbekyan et.
A Neural Network Ensemble Approach to System Identification
Given samples of solutions $x(t)$ to an unknown dynamical system $\dot{x}(t)=f(t, x(t))$, we approximate the function $f$ using an ensemble of neural networks.
System Identification Through Lipschitz Regularized Deep Neural Networks
In this paper we use neural networks to learn governing equations from data.
