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09/09/2023
RRCNN^+: An Enhanced Residual Recursive Convolutional Neural Network for Non-stationary Signal Decomposition
Time-frequency analysis is an important and challenging task in many app...
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07/04/2023
RRCNN: A novel signal decomposition approach based on recurrent residue convolutional neural network
The decomposition of non-stationary signals is an important and challeng...
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06/29/2023
Why Shallow Networks Struggle with Approximating and Learning High Frequency: A Numerical Study
In this work, a comprehensive numerical study involving analysis and exp...
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05/31/2023
Parameterized Wasserstein Hamiltonian Flow
In this work, we propose a numerical method to compute the Wasserstein H...
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01/31/2023
Neural Control of Parametric Solutions for High-dimensional Evolution PDEs
We develop a novel computational framework to approximate solution opera...
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09/12/2022
Optimal control for stochastic nonlinear Schrodinger equation on graph
We study the optimal control formulation for stochastic nonlinear Schrod...
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06/29/2022
Discrete Langevin Sampler via Wasserstein Gradient Flow
Recently, a family of locally balanced (LB) samplers has demonstrated ex...
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05/31/2022
New theoretical insights in the decomposition and time-frequency representation of nonstationary signals: the IMFogram algorithm
The analysis of the time-frequency content of a signal is a classical pr...
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11/23/2021
One or two frequencies? The Iterative Filtering answers
The Iterative Filtering method is a technique aimed at the decomposition...
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06/07/2021
Scalable Computation of Monge Maps with General Costs
Monge map refers to the optimal transport map between two probability di...
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05/20/2021
A continuation multiple shooting method for Wasserstein geodesic equation
In this paper, we propose a numerical method to solve the classic L^2-op...
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03/14/2021
Mean Field Game GAN
We propose a novel mean field games (MFGs) based GAN(generative adversar...
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02/05/2021
Learning High Dimensional Wasserstein Geodesics
We propose a new formulation and learning strategy for computing the Was...
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11/28/2020
Time-frequency representation of nonstationary signals: the FIFogram
Iterative filtering methods were introduced around 2010 to improve defin...
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06/16/2020
Time Discretizations of Wasserstein-Hamiltonian Flows
We study discretizations of Hamiltonian systems on the probability densi...
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02/26/2020
Numerical Solution of Inverse Problems by Weak Adversarial Networks
We consider a weak adversarial network approach to numerically solve a c...
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02/22/2020
Learning Cost Functions for Optimal Transport
Learning the cost function for optimal transport from observed transport...
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02/10/2020
Learning Stochastic Behaviour of Aggregate Data
Learning nonlinear dynamics of aggregate data is a challenging problem s...
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09/25/2019
Path Planning in Unknown Environments Using Optimal Transport Theory
This paper introduces a graph-based, potential-guided method for path pl...
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07/18/2019
Weak Adversarial Networks for High-dimensional Partial Differential Equations
Solving general high-dimensional partial differential equations (PDE) is...
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02/10/2018
Learning to Recommend via Inverse Optimal Matching
We consider recommendation in the context of optimal matching, i.e., we ...
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12/07/2015