:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Cho, Hyunwoo, Jo, Hyeontae, Hwang, Hyung Ju
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Dynamical Systems 68T07, 68T05, 70G60
Online Access:	https://arxiv.org/abs/2507.10884
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Estimation of System Parameters Including Repeated Cross-Sectional Data through Emulator-Informed Deep Generative Model
by: Cho, Hyunwoo, et al.
Published: (2024)

Machine learning-based vorticity evolution and superresolution of homogeneous isotropic turbulence using wavelet projection
by: Asaka, Tomoki, et al.
Published: (2024)

Estimating the Distribution of Parameters in Differential Equations with Repeated Cross-Sectional Data
by: Jo, Hyeontae, et al.
Published: (2024)

Deep Predictor-Corrector Networks for Robust Parameter Estimation in Non-autonomous System with Discontinuous Inputs
by: Gu, Gyeongwan, et al.
Published: (2026)

Pseudo-Differential Neural Operator: Generalized Fourier Neural Operator for Learning Solution Operators of Partial Differential Equations
by: Shin, Jin Young, et al.
Published: (2022)

A parametric approach to the estimation of convex risk functionals based on Wasserstein distance
by: Nendel, Max, et al.
Published: (2022)

Computing Systemic Risk Measures with Graph Neural Networks
by: Gonon, Lukas, et al.
Published: (2024)

Flexible and efficient emulation of spatial extremes processes via variational autoencoders
by: Zhang, Likun, et al.
Published: (2023)

Differentiable Neural Networks with RePU Activation: with Applications to Score Estimation and Isotonic Regression
by: Shen, Guohao, et al.
Published: (2023)

Neural Network-Based Parameter Estimation for Non-Autonomous Differential Equations with Discontinuous Signals
by: Jo, Hyeontae, et al.
Published: (2025)

Bifidelity Karhunen-Loève Expansion Surrogate with Active Learning for Random Fields
by: Jivani, Aniket, et al.
Published: (2025)

Learning collective variables that preserve transition rates
by: Sule, Shashank, et al.
Published: (2025)

Graphs whose vertices of degree at least 2 lie in a triangle
by: Forte, Vinicius L. do, et al.
Published: (2022)

A Unified Framework for Critical Scaling of Inverse Temperature in Self-Attention
by: Hayase, Tomohiro, et al.
Published: (2026)

Generalization Error of GAN from the Discriminator's Perspective
by: Yang, Hongkang, et al.
Published: (2021)

Error analysis for learning fractional stochastic differential equations with applications in neural approximations
by: Dehshiri, Mahdi, et al.
Published: (2026)

Kernel Limit for a Class of Recurrent Neural Networks Trained on Ergodic Data Sequences
by: Lam, Samuel Chun-Hei, et al.
Published: (2023)

Mathematical Foundations of Neural Tangents and Infinite-Width Networks
by: Mysore, Rachana, et al.
Published: (2025)

A Low-complexity Structured Neural Network to Realize States of Dynamical Systems
by: Aluvihare, Hansaka, et al.
Published: (2025)

Phase Transitions in the Fluctuations of Functionals of Random Neural Networks
by: Di Lillo, Simmaco, et al.
Published: (2026)

Convergence Analysis of Real-time Recurrent Learning (RTRL) for a class of Recurrent Neural Networks
by: Lam, Samuel Chun-Hei, et al.
Published: (2025)

Wide neural networks with general weights: convergence rate and explicit dependence on the hyper-parameters
by: Celli, Lucia
Published: (2026)

Learn and Verify: A Framework for Rigorous Verification of Physics-Informed Neural Networks
by: Tanaka, Kazuaki, et al.
Published: (2026)

Conditional Stochastic Interpolation for Generative Learning
by: Huang, Ding, et al.
Published: (2023)

Designing Poisson Integrators Through Machine Learning
by: Vaquero, Miguel, et al.
Published: (2024)

Mixed memories in Hopfield networks
by: Gayrard, Véronique
Published: (2025)

Large and moderate deviations for Gaussian neural networks
by: Macci, Claudio, et al.
Published: (2024)

Transfer Learning through Enhanced Sufficient Representation: Enriching Source Domain Knowledge with Target Data
by: Ge, Yeheng, et al.
Published: (2025)

A Theory of Non-Acyclic Generative Flow Networks
by: Brunswic, Leo Maxime, et al.
Published: (2023)

Incremental Certificate Learning for Hybrid Neural Network Verification . A Solver Architecture for Piecewise-Linear Safety Queries
by: Gokavarapu, Chandrasekhar
Published: (2025)

The Boundaries of Verifiable Accuracy, Robustness, and Generalisation in Deep Learning
by: Bastounis, Alexander, et al.
Published: (2023)

Convolutional Attention in Betting Exchange Markets
by: Gonçalves, Rui, et al.
Published: (2025)

Large deviation principles and functional limit theorems in the deep limit of wide random neural networks
by: Di Lillo, Simmaco, et al.
Published: (2026)

Fair Sufficient Representation Learning
by: Zhou, Xueyu, et al.
Published: (2025)

Convergence of Continuous Normalizing Flows for Learning Probability Distributions
by: Gao, Yuan, et al.
Published: (2024)

The random $k$-SAT Gibbs uniqueness threshold revisited
by: Chatterjee, Arnab, et al.
Published: (2025)

Neural Network Localized Orthogonal Decomposition for Numerical Homogenization of Diffusion Operators with Random Coefficients
by: Kröpfl, Fabian, et al.
Published: (2025)

Wasserstein Distributionally Robust Nonparametric Regression
by: Liu, Changyu, et al.
Published: (2025)

Deep Operator BSDE: a Numerical Scheme to Approximate Solution Operators
by: Lozano, Pere Díaz, et al.
Published: (2024)

Neural Networks-based Random Vortex Methods for Modelling Incompressible Flows
by: Cherepanov, Vladislav, et al.
Published: (2024)