:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Krämer, Nicholas
Format:	Preprint
Published:	2024
Subjects:	Numerical Analysis Machine Learning Systems and Control Computation
Online Access:	https://arxiv.org/abs/2409.20004
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

From Cursed to Competitive: Closing the ZO-FO Gap via Input-to-State Stability
by: Farzin, Amir Ali, et al.
Published: (2026)

Adaptive Probabilistic ODE Solvers Without Adaptive Memory Requirements
by: Krämer, Nicholas
Published: (2024)

Numerically robust Gaussian state estimation with singular observation noise
by: Krämer, Nicholas, et al.
Published: (2025)

Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
by: Zaspel, Peter, et al.
Published: (2024)

Physics-Informed Machine Learning for Characterizing System Stability
by: Koike, Tomoki, et al.
Published: (2025)

Neural network-enhanced integrators for simulating ordinary differential equations
by: Othmane, Amine, et al.
Published: (2025)

PINNSim: A Simulator for Power System Dynamics based on Physics-Informed Neural Networks
by: Stiasny, Jochen, et al.
Published: (2023)

A comparison between joint and dual UKF implementations for state estimation and leak localization in water distribution networks
by: Romero-Ben, Luis, et al.
Published: (2025)

On the Stability Connection Between Discrete-Time Algorithms and Their Resolution ODEs: Applications to Min-Max Optimisation
by: Farzin, Amir Ali, et al.
Published: (2026)

On the Width Scaling of Neural Optimizers Under Matrix Operator Norms I: Row/Column Normalization and Hyperparameter Transfer
by: Xu, Ruihan, et al.
Published: (2026)

ZORMS-LfD: Learning from Demonstrations with Zeroth-Order Random Matrix Search
by: Dry, Olivia, et al.
Published: (2025)

Symmetric Hermite quadrature-based balanced truncation for learning linear dynamical systems from derivative data
by: Reiter, Sean, et al.
Published: (2026)

Kernel Methods for Stochastic Dynamical Systems with Application to Koopman Eigenfunctions: Feynman-Kac Representations and RKHS Approximation
by: Hamzi, Boumediene, et al.
Published: (2026)

Error Bounds for Physics-Informed Neural Networks in Fokker-Planck PDEs
by: Kong, Chun-Wei, et al.
Published: (2024)

On Approximate Computation of Critical Points
by: Ahmadi, Amir Ali, et al.
Published: (2026)

A Provably-Correct and Robust Convex Model for Smooth Separable NMF
by: Pan, Junjun, et al.
Published: (2025)

Competitive Physics Informed Networks
by: Zeng, Qi, et al.
Published: (2022)

From Adam to Adam-Like Lagrangians: Second-Order Nonlocal Dynamics
by: Heredia, Carlos
Published: (2026)

Randomized Space-Time Sampling for Affine Graph Dynamical Systems
by: Gong, Le, et al.
Published: (2025)

The Vanishing Gradient Problem for Stiff Neural Differential Equations
by: Fronk, Colby, et al.
Published: (2025)

Continuous Data Assimilation with Learned Surrogate Dynamics
by: Li, Wenwen, et al.
Published: (2026)

Creating walls to avoid unwanted points in root finding and optimization
by: Truong, Tuyen Trung
Published: (2023)

Optimizing Hard Thresholding for Sparse Model Discovery
by: Jollie, Derek W., et al.
Published: (2025)

Trustworthy Koopman Operator Learning: Invariance Diagnostics and Error Bounds
by: Conradie, Gustav, et al.
Published: (2026)

Symmetry & Critical Points
by: Arjevani, Yossi
Published: (2024)

Operator Learning for Smoothing and Forecasting
by: Calvello, Edoardo, et al.
Published: (2026)

On the Convergence of the Gradient Descent Method with Stochastic Fixed-point Rounding Errors under the Polyak-Lojasiewicz Inequality
by: Xia, Lu, et al.
Published: (2023)

sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation
by: Xu, Renjie, et al.
Published: (2025)

Improving Numerical Stability and Accuracy in Partitioned Methods with Algebraic Prediction
by: Ali, Ahmad, et al.
Published: (2024)

A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method
by: Fang, Yuchen, et al.
Published: (2026)

WinQ: Accelerating Quantization-Aware Training of Language Models Around Saddle Points
by: Li, Dongyue, et al.
Published: (2026)

Implementing PID Controller on a hand follower robot using Numerical Methods
by: Mostafa, Mostafa A., et al.
Published: (2025)

Multiplicative Dynamic Mode Decomposition
by: Boullé, Nicolas, et al.
Published: (2024)

Backtracking New Q-Newton's method, Newton's flow, Voronoi's diagram and Stochastic root finding
by: Fornaess, John Erik, et al.
Published: (2024)

Rigged Dynamic Mode Decomposition: Data-Driven Generalized Eigenfunction Decompositions for Koopman Operators
by: Colbrook, Matthew J., et al.
Published: (2024)

Limits and Powers of Koopman Learning
by: Colbrook, Matthew J., et al.
Published: (2024)

An Introductory Guide to Koopman Learning
by: Colbrook, Matthew J., et al.
Published: (2025)

Trust-Region Sequential Quadratic Programming for Stochastic Optimization with Random Models
by: Fang, Yuchen, et al.
Published: (2024)

Modified Loss of Momentum Gradient Descent: Fine-Grained Analysis
by: Cattaneo, Matias D., et al.
Published: (2025)

Online Covariance Matrix Estimation in Sketched Newton Methods
by: Kuang, Wei, et al.
Published: (2025)