:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gallon, Davide, von Wurstemberger, Philippe, Cheridito, Patrick, Jentzen, Arnulf
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition Numerical Analysis
Online Access:	https://arxiv.org/abs/2602.09708
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An overview of diffusion models for generative artificial intelligence
by: Gallon, Davide, et al.
Published: (2024)

Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory
by: Jentzen, Arnulf, et al.
Published: (2023)

High-dimensional approximation spaces of artificial neural networks and applications to partial differential equations
by: Beneventano, Pierfrancesco, et al.
Published: (2020)

Algorithmically Designed Artificial Neural Networks (ADANNs): Higher order deep operator learning for parametric partial differential equations
by: Jentzen, Arnulf, et al.
Published: (2023)

An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning
by: Gonon, Lukas, et al.
Published: (2024)

Deep learning based numerical approximation algorithms for stochastic partial differential equations
by: Beck, Christian, et al.
Published: (2020)

INEUS: Iterative Neural Solver for High-Dimensional PIDEs
by: Dupret, Jean-Loup, et al.
Published: (2026)

DiffusionPDE: Generative PDE-Solving Under Partial Observation
by: Huang, Jiahe, et al.
Published: (2024)

DBMSolver: A Training-free Diffusion Bridge Sampler for High-Quality Image-to-Image Translation
by: Venugopal, Sankarshana, et al.
Published: (2026)

Recursive Flow Matching
by: Huang, Jiahe, et al.
Published: (2026)

A generalizable framework for low-rank tensor completion with numerical priors
by: Yuan, Shiran, et al.
Published: (2023)

Robust Training of Neural Networks at Arbitrary Precision and Sparsity
by: Ye, Chengxi, et al.
Published: (2024)

Group and Shuffle: Efficient Structured Orthogonal Parametrization
by: Gorbunov, Mikhail, et al.
Published: (2024)

Deep Guess acceleration for explainable image reconstruction in sparse-view CT
by: Piccolomini, Elena Loli, et al.
Published: (2024)

High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers
by: Wodzinski, Marek, et al.
Published: (2023)

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction
by: Mohan, K. Aditya, et al.
Published: (2024)

Convergence rates for gradient descent in the training of overparameterized artificial neural networks with piecewise affine activation
by: Jentzen, Arnulf, et al.
Published: (2021)

Tensor PCA from basis in tensor space
by: Turchetti, Claudio, et al.
Published: (2023)

MC$^2$: Monte Carlo Correction for Fast Elliptic PDE Solving
by: Hsu, Ethan, et al.
Published: (2026)

Towards Spatio-Temporal Extrapolation of Phase-Field Simulations with Convolution-Only Neural Networks
by: Bonneville, Christophe, et al.
Published: (2026)

A brief review of the Deep BSDE method for solving high-dimensional partial differential equations
by: Han, Jiequn, et al.
Published: (2025)

Deep neural network approximation theory for high-dimensional functions
by: Beneventano, Pierfrancesco, et al.
Published: (2021)

Learning the random variables in Monte Carlo simulations with stochastic gradient descent: Machine learning for parametric PDEs and financial derivative pricing
by: Becker, Sebastian, et al.
Published: (2022)

Space-time deep neural network approximations for high-dimensional partial differential equations
by: Hornung, Fabian, et al.
Published: (2020)

A Novel Wasserstein Quaternion Generative Adversarial Network for Color Image Generation
by: Jia, Zhigang, et al.
Published: (2025)

Fast OTSU Thresholding Using Bisection Method
by: Kodathala, Sai Varun
Published: (2025)

Synergizing Multigrid Algorithms with Vision Transformer: A Novel Approach to Enhance the Seismic Foundation Model
by: Wu, Huiwen, et al.
Published: (2025)

Deep Neural Networks Inspired by Differential Equations
by: Liu, Yongshuai, et al.
Published: (2025)

Learning rate adaptive stochastic gradient descent optimization methods: numerical simulations for deep learning methods for partial differential equations and convergence analyses
by: Dereich, Steffen, et al.
Published: (2024)

PADAM: Parallel averaged Adam reduces the error for stochastic optimization in scientific machine learning
by: Jentzen, Arnulf, et al.
Published: (2025)

Averaged Adam accelerates stochastic optimization in the training of deep neural network approximations for partial differential equation and optimal control problems
by: Dereich, Steffen, et al.
Published: (2025)

The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks
by: Bastounis, Alexander, et al.
Published: (2021)

Linearized Attention Cannot Enter the Kernel Regime at Any Practical Width
by: Miñoza, Jose Marie Antonio, et al.
Published: (2026)

Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups
by: Shumaylov, Zakhar, et al.
Published: (2024)

Layer-Specific Optimization: Sensitivity Based Convolution Layers Basis Search
by: Alekseev, Vasiliy, et al.
Published: (2024)

Multiresolution local smoothness detection in non-uniformly sampled multivariate signals
by: Avesani, Sara, et al.
Published: (2025)

A Proper Orthogonal Decomposition approach for parameters reduction of Single Shot Detector networks
by: Meneghetti, Laura, et al.
Published: (2022)

Solutions to Elliptic and Parabolic Problems via Finite Difference Based Unsupervised Small Linear Convolutional Neural Networks
by: Celaya, Adrian, et al.
Published: (2023)

LAMA: Stable Dual-Domain Deep Reconstruction For Sparse-View CT
by: Ding, Chi, et al.
Published: (2024)

MgNet: A Unified Framework of Multigrid and Convolutional Neural Network
by: He, Juncai, et al.
Published: (2019)