DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method
We introduce DeepParticle, a method to learn and generate invariant measures of stochastic
dynamical systems with physical parameters based on data computed from an interacting …
dynamical systems with physical parameters based on data computed from an interacting …
A convergent interacting particle method for computing KPP front speeds in random flows
We aim to efficiently compute spreading speeds of reaction-diffusion-advection (RDA) fronts
in divergence free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) …
in divergence free random flows under the Kolmogorov-Petrovsky-Piskunov (KPP) …
A DeepParticle method for learning and generating aggregation patterns in multi-dimensional Keller–Segel chemotaxis systems
We study a regularized interacting particle method for computing aggregation patterns and
near singular solutions of a Keller–Segel (KS) chemotaxis system in two and three space …
near singular solutions of a Keller–Segel (KS) chemotaxis system in two and three space …
Lagrangian, game theoretic, and PDE methods for averaging G-equations in turbulent combustion: existence and beyond
G-equations are popular level set Hamilton–Jacobi nonlinear partial differential equations
(PDEs) of first or second order arising in turbulent combustion. Characterizing the effective …
(PDEs) of first or second order arising in turbulent combustion. Characterizing the effective …
Residual Diffusivity for Noisy Bernoulli Maps
G Iyer, J Nolen - arXiv preprint arXiv:2409.12410, 2024 - arxiv.org
Consider a discrete time Markov process $ X^\varepsilon $ on $\mathbb R^ d $ that makes a
deterministic jump prescribed by a map $\varphi\colon\mathbb R^ d\to\mathbb R^ d $, and …
deterministic jump prescribed by a map $\varphi\colon\mathbb R^ d\to\mathbb R^ d $, and …
An augmented subspace based adaptive proper orthogonal decomposition method for time dependent partial differential equations
In this paper, we propose an augmented subspace based adaptive proper orthogonal
decomposition (POD) method for solving the time dependent partial differential equations …
decomposition (POD) method for solving the time dependent partial differential equations …
Long time asymptotics of mixed-type Kimura diffusions
This paper concerns the long-time asymptotics of diffusions with degenerate coefficients at
the domain's boundary. Degenerate diffusion operators with mixed linear and quadratic …
the domain's boundary. Degenerate diffusion operators with mixed linear and quadratic …
Reweighted Interacting Langevin Diffusions: an Accelerated Sampling Methodfor Optimization
We proposed a new technique to accelerate sampling methods for solving difficult
optimization problems. Our method investigates the intrinsic connection between posterior …
optimization problems. Our method investigates the intrinsic connection between posterior …
Partial Differential Equations Arising from Topological Insulators
B Chen - 2024 - knowledge.uchicago.edu
In this thesis, we develop a scattering theory for the asymmetric transport observed at
interfaces separating two-dimensional topological insulators. Starting from the spectral …
interfaces separating two-dimensional topological insulators. Starting from the spectral …
[PDF][PDF] A Bibliography of Publications in SIAM Journal on Numerical Analysis: 2010–2019
NHF Beebe - 2024 - ctan.math.utah.edu
A Bibliography of Publications in SIAM Journal on Numerical Analysis: 2010–2019 Page 1
A Bibliography of Publications in SIAM Journal on Numerical Analysis: 2010–2019 Nelson …
A Bibliography of Publications in SIAM Journal on Numerical Analysis: 2010–2019 Nelson …