Image de couverture de livre

Manifold limit for the training of shallow graph convolutional neural networks

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Tengler, Johanna, Brune, Christoph, Iglesias, José A.
Format:	Preprint
Publié:	2026
Sujets:	Machine Learning Functional Analysis Optimization and Control 68T07, 46N10, 49J45, 58J50 G.1.2; I.2.6; I.5.1; G.1.6
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Physics Informed Differentiable Solvers for Learning Parametric Solution Manifolds in Heterogeneous Physical Systems
par: Panahi, Milad, et autres
Publié: (2026)

Contrastive and Multi-Task Learning on Noisy Brain Signals with Nonlinear Dynamical Signatures
par: Ghosh, Sucheta, et autres
Publié: (2026)

Causal Portfolio Optimization: Principles and Sensitivity-Based Solutions
par: Dominguez, Alejandro Rodriguez
Publié: (2025)

Causal PDE-Control Models for Dynamic Portfolio Optimization with Latent Drivers
par: Dominguez, Alejandro Rodriguez
Publié: (2025)

Signal from Noise Signal from Noise: A Neural Network-Based Denoising Approach for Measuring Global Financial Spillovers
par: Karasan, Abdullah, et autres
Publié: (2025)

Vector-Valued Reproducing Kernel Banach Spaces for Neural Networks and Operators
par: Dummer, Sven, et autres
Publié: (2025)

Leveraging Causal Reasoning Method for Explaining Medical Image Segmentation Models
par: Jiang, Limai, et autres
Publié: (2026)

A Benchmark of Classical and Deep Learning Models for Agricultural Commodity Price Forecasting on A Novel Bangladeshi Market Price Dataset
par: Muhammad, Tashreef, et autres
Publié: (2026)

Learning Explicit Single-Cell Dynamics Using ODE Representations
par: von Bassewitz, Jan-Philipp, et autres
Publié: (2025)

Location based Probabilistic Load Forecasting of EV Charging Sites: Deep Transfer Learning with Multi-Quantile Temporal Convolutional Network
par: Ali, Mohammad Wazed, et autres
Publié: (2024)

Non-Heuristic Selection via Hybrid Regularized and Machine Learning Models for Insurance
par: Galvão, Luciano Ribeiro, et autres
Publié: (2025)

A well-posed variational approach to the identification and convergent approximation of material laws from boundary data
par: Conti, Sergio, et autres
Publié: (2025)

Latent Space Representation of Electricity Market Curves: Maintaining Structural Integrity
par: Výboh, Martin, et autres
Publié: (2025)

Deep Learning for Solving and Estimating Dynamic Models in Economics and Finance
par: Scheidegger, Simon
Publié: (2026)

From Articles to Canopies: Knowledge-Driven Pseudo-Labelling for Tree Species Classification using LLM Experts
par: Romaszewski, Michał, et autres
Publié: (2026)

Challenges in automatic differentiation and numerical integration in physics-informed neural networks modelling
par: Daněk, Josef, et autres
Publié: (2024)

Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization
par: Duswald, Tobias, et autres
Publié: (2024)

Local properties of neural networks through the lens of layer-wise Hessians
par: Bolshim, Maxim, et autres
Publié: (2025)

JacNet: Learning Functions with Structured Jacobians
par: Lorraine, Jonathan, et autres
Publié: (2024)

Deep Policy Iteration with Integer Programming for Inventory Management
par: Harsha, Pavithra, et autres
Publié: (2021)

Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks
par: Høyheim, Eirik, et autres
Publié: (2025)

Bayesian Generalized Nonlinear Models Offer Basis Free SINDy With Model Uncertainty
par: Hubin, Aliaksandr
Publié: (2025)

FBMS: An R Package for Flexible Bayesian Model Selection and Model Averaging
par: Frommlet, Florian, et autres
Publié: (2025)

Asset Pricing in Pre-trained Transformer
par: Lai, Shanyan
Publié: (2025)

Active Learning for Conditional Generative Compressed Sensing
par: DeLise, Alexander, et autres
Publié: (2026)

When Reasoning Fails: Evaluating 'Thinking' LLMs for Stock Prediction
par: Sodha, Rakeshkumar H
Publié: (2025)

Analysis of Galactic cirrus filaments in HSC-SSP high-resolution deep images using artificial neural networks
par: Poliakov, Denis M., et autres
Publié: (2026)

VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks
par: Johnson, David R., et autres
Publié: (2025)

Cryptogenic stroke and migraine: using probabilistic independence and machine learning to uncover latent sources of disease from the electronic health record
par: Betts, Joshua W., et autres
Publié: (2025)

Assessing the Performance-Efficiency Trade-off of Foundation Models in Probabilistic Electricity Price Forecasting
par: Lettner, Jan Niklas, et autres
Publié: (2026)

EchoLSTM: A Self-Reflective Recurrent Network for Stabilizing Long-Range Memory
par: K, Prasanth K, et autres
Publié: (2025)

TCRTransBench: A Comprehensive Benchmark for Bidirectional TCR-Peptide Sequence Generation
par: Wang, Yiming, et autres
Publié: (2026)

Towards Automated Diagnosis of Inherited Arrhythmias: Combined Arrhythmia Classification Using Lead-Aware Spatial Attention Networks
par: Sigfstead, Sophie, et autres
Publié: (2026)

DeepDTF: Dual-Branch Transformer Fusion for Multi-Omics Anticancer Drug Response Prediction
par: Zhao, Yuhan, et autres
Publié: (2026)

Predicting California Bearing Ratio with Ensemble and Neural Network Models: A Case Study from Turkiye
par: Kökçam, Abdullah Hulusi, et autres
Publié: (2025)

GRALIS: A Unified Canonical Framework for Linear Attribution Methods via Riesz Representation
par: Fanale, Raimondo
Publié: (2026)

Scalable and Interpretable Scientific Discovery via Sparse Variational Gaussian Process Kolmogorov-Arnold Networks (SVGP KAN)
par: Ju, Y. Sungtaek
Publié: (2025)

Uncertainty Quantification for Scientific Machine Learning using Sparse Variational Gaussian Process Kolmogorov-Arnold Networks (SVGP KAN)
par: Ju, Y. Sungtaek
Publié: (2025)

Bridging Scales: a Hybrid Model to Simulate Vascular Tumor Growth and Treatment Response
par: Duswald, Tobias, et autres
Publié: (2023)

Stochastic Estimation of the Layer-wise Hessian Trace for Monitoring Neural-network Training
par: Bolshim, Maxim, et autres
Publié: (2026)