Cover Image

Leveraging Real-Time Data Analysis and Multiple Kernel Learning for Manufacturing of Innovative Steels

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rannetbauer, Wolfgang, Hubmer, Simon, Hambrock, Carina, Ramlau, Ronny
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Predictive Modelling of Critical Variables for Improving HVOF Coating using Gamma Regression Models
by: Rannetbauer, Wolfgang, et al.
Published: (2023)

A Practical Guide to Optimizing Industrial Thermal Spraying through Comparative Multi-Objective Optimization
by: Rannetbauer, Wolfgang, et al.
Published: (2025)

On SCD Semismooth$^*$ Newton methods for the efficient minimization of Tikhonov functionals with non-smooth and non-convex penalties
by: Gfrerer, Helmut, et al.
Published: (2024)

A Geometrical Acoustics based Focusing Algorithm for Layered Media in Medical Ultrasound
by: Hackl, Simon, et al.
Published: (2025)

Regularization of linear inverse problems with irregular noise using embedding operators
by: Li, Xinyan, et al.
Published: (2024)

Singular Value and Frame Decomposition-based Reconstruction for Atmospheric Tomography
by: Weissinger, Lukas, et al.
Published: (2024)

Singular Value-based Atmospheric Tomography with Fourier Domain Regularization (SAFR)
by: Weissinger, Lukas, et al.
Published: (2025)

On Phase Unwrapping via Digital Wavefront Sensors
by: Hubmer, Simon, et al.
Published: (2024)

Efficient TV regularization of large-scale linear inverse problems via the SCD semismooth* Newton method with applications in tomography
by: Gfrerer, Helmut, et al.
Published: (2026)

An Inverse Problems Approach to Pulse Wave Analysis in the Human Brain
by: Weissinger, Lukas, et al.
Published: (2024)

Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
by: Jalalian, Yasamin, et al.
Published: (2025)

Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling
by: Chatalic, Antoine, et al.
Published: (2023)

On the Intensity-based Inversion Method for Quantitative Quasi-Static Elastography
by: Sherina, Ekaterina, et al.
Published: (2025)

Sketching the Heat Kernel: Using Gaussian Processes to Embed Data
by: Gilbert, Anna C., et al.
Published: (2024)

Data-efficient Kernel Methods for Learning Hamiltonian Systems
by: Jalalian, Yasamin, et al.
Published: (2025)

Fast Evaluation of Additive Kernels: Feature Arrangement, Fourier Methods, and Kernel Derivatives
by: Wagner, Theresa, et al.
Published: (2024)

An Orthogonal Polynomial Kernel-Based Machine Learning Model for Differential-Algebraic Equations
by: Taheri, Tayebeh, et al.
Published: (2024)

Scalable Signature Kernel Computations for Long Time Series via Local Neumann Series Expansions
by: Tamayo-Rios, Matthew, et al.
Published: (2025)

Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
by: Lowery, Matthew, et al.
Published: (2024)

KROM: Kernelized Reduced Order Modeling
by: Bacho, Aras, et al.
Published: (2026)

Giga-scale Kernel Matrix Vector Multiplication on GPU
by: Hu, Robert, et al.
Published: (2022)

On a PDE-based material parameter identification problem with contact constraints
by: Hubmer, Simon, et al.
Published: (2026)

Fast Spectrum Estimation of Some Kernel Matrices
by: Lepilov, Mikhail
Published: (2024)

On the Convergence of Irregular Sampling in Reproducing Kernel Hilbert Spaces
by: Iske, Armin
Published: (2025)

Ensemble Score Filtering for Real-Data Energy Consumption Forecast Correction
by: Hu, Ruoyu, et al.
Published: (2026)

Deflation-PINNs: Learning Multiple Solutions for PDEs and Landau-de Gennes
by: Disarò, Sean, et al.
Published: (2026)

A Hybrid Kernel-Free Boundary Integral Method with Operator Learning for Solving Parametric Partial Differential Equations In Complex Domains
by: Ling, Shuo, et al.
Published: (2024)

On Quasi-Localized Dual Pairs in Reproducing Kernel Hilbert Spaces
by: Harbrecht, Helmut, et al.
Published: (2024)

On some analytic properties of the atmospheric tomography operator: Non-Uniqueness and reconstructability issues
by: Ramlau, Ronny, et al.
Published: (2024)

Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms
by: Hertrich, Johannes
Published: (2024)

Leveraging time and parameters for nonlinear model reduction methods
by: Glas, Silke, et al.
Published: (2025)

Solving Roughly Forced Nonlinear PDEs via Misspecified Kernel Methods and Neural Networks
by: Baptista, Ricardo, et al.
Published: (2025)

Operator Learning: Algorithms and Analysis
by: Kovachki, Nikola B., et al.
Published: (2024)

Data Complexity Estimates for Operator Learning
by: Kovachki, Nikola B., et al.
Published: (2024)

Orthonormal Expansions for Translation-Invariant Kernels
by: Tronarp, Filip, et al.
Published: (2022)

Convergence and Sketching-Based Efficient Computation of Neural Tangent Kernel Weights in Physics-Based Loss
by: Hirsch, Max, et al.
Published: (2025)

Large Data Limits of Laplace Learning for Gaussian Measure Data in Infinite Dimensions
by: Zhong, Zhengang, et al.
Published: (2026)

Quantum Harmonic Analysis and the Structure in Data: Augmentation
by: Doerfler, Monika, et al.
Published: (2025)

A Kernel-based Stochastic Approximation Framework for Nonlinear Operator Learning
by: Yang, Jia-Qi, et al.
Published: (2025)

A Dictionary of Closed-Form Kernel Mean Embeddings
by: Briol, François-Xavier, et al.
Published: (2025)