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Papers matching “neural network approximation” 68

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Generalizing neural network verification to the family of piece-wise linear activation functions
2025 Science of Computer Programming article Computer Science Formal Methods in Verification Open access

László Antal, Erika Ábrahám, Hana Masara

3

citations
Extending Neural Network Verification to a Larger Family of Piece-wise Linear Activation Functions
2023 Electronic Proceedings in Theoretical Computer Science article Computer Science Formal Methods in Verification Open access

László Antal, Hana Masara, Erika Ábrahám

4

citations
Counterexample-Guided Abstraction Refinement for Star-Based Neural Network Verification
2025 Lecture notes in computer science conference-paper Computer Science Formal Methods in Verification

László Antal, Erika Ábrahám

0

citations
Synthesis and analysis of neural-network-based control in cyber-physical systems
2026 RWTH Publications (RWTH Aachen) dissertation Computer Science Formal Methods in Verification Open access

László Antal

0

citations
Smaller generalization error derived for a deep residual neural network compared with shallow networks
2022 IMA Journal of Numerical Analysis article Computer Science Stochastic Gradient Optimization Techniques Open access

Aku Kammonen, Jonas Kiessling, Petr Plecháč, Mattias Sandberg, Anders Szepessy, Raul F. Tempone

4

citations
Provably Bounding Neural Network Preimages
2023 arXiv (Cornell University) preprint Computer Science Formal Methods in Verification Open access

Suhas Kotha, Christopher Brix, J. Zico Kolter, Krishnamurthy

6

citations
On the Interpretability of Neural Network Decoders
2025 Advanced Quantum Technologies article Computer Science Quantum Computing Algorithms and Architecture Open access

Lukas Bödeker, Luc J. B. Kusters, Markus Michael Müller

0

citations
Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples
2021 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Christian Fiedler, Massimo Fornasier, Timo Klock, Michael Rauchensteiner

0

citations
A theory of data variability in Neural Network Bayesian inference
2023 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias

0

citations
Data variability in neural network Bayesian inference
2025 Physical Review Research article Computer Science Gaussian Processes and Bayesian Inference Open access

0

citations
Points of non-linearity of functions generated by random neural networks
2023 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

0

citations
Uncovering a Universal Abstract Algorithm for Modular Addition in Neural Networks
2025 neural information processing systems conference-paper Computer Science Neural Networks and Applications Open access

Gavin McCracken, Gabriela Moisescu-Pareja, Vincent Létourneau, Doina Precup

0

citations
Automated Design of Linear Bounding Functions for Sigmoidal Nonlinearities in Neural Networks
2024 arXiv (Cornell University) preprint Computer Science Adversarial Robustness in Machine Learning Open access

Xiyue Zhang, Holger H. Hoos, Marta Kwiatkowska, Jan N. van Rijn

0

citations
Fine-grained Expressivity of Graph Neural Networks
2023 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Jan Böker, Ron Levie, Ningyuan Teresa Huang, Soledad Villar

4

citations
A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control
2024 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Mathias Oster, Luca Saluzzi, Tizian Wenzel

1

citations
Discovering uncertainty: Bayesian constitutive artificial neural networks
2024 Computer Methods in Applied Mechanics and Engineering article Computer Science Gaussian Processes and Bayesian Inference Open access

Kevin Linka, Gerhard A. Holzapfel, Ellen Kuhl

37

citations
Discovering uncertainty: Bayesian constitutive artificial neural networks
2024 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Kevin Linka, Gerhard A. Holzapfel, Ellen Kuhl

6

citations
The Surprising Power of Graph Neural Networks with Random Node Initialization
2021 conference-paper Computer Science Advanced Graph Neural Networks Open access cited by 1 patent

Ralph Abboud, İsmail İlkan Ceylan, Martin Grohe, Thomas Lukasiewicz

14

citations
Convolutional neural networks for quantitative smartphone video nystagmography: ConVNG
2022 medRxiv preprint Computer Science Gaze Tracking and Assistive Technology Open access

Maximilian Uwe Friedrich, Erich Schneider, Miriam Buerklein, Johannes Taeger, Johannes Hartig, Jens Volkmann, +2 more

0

citations
Optimized Convolutional Neural Networks for Video Intra Prediction
2020 Proceedings - International Conference on Image Processing conference-paper Computer Science Video Coding and Compression Technologies

Jonathan Wiesner, Christian Rohlfing

1

citations
From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning
2025 JuSER (Forschungszentrum Jülich) conference-paper Computer Science Neural Networks and Applications Open access

Noa Rubin, Javed Lindner, David Dahmen, Inbar Seroussi, Zohar Ringel, M. Krämer, +1 more

0

citations
The Kolmogorov–Arnold representation theorem revisited
2021 Neural Networks article Computer Science Neural Networks and Applications Open access

Johannes Schmidt-Hieber

5

citations
The Kolmogorov–Arnold representation theorem revisited
2021 University of Twente Research Information article Computer Science Neural Networks and Applications Open access

283

citations
Approximation and Generalization Capacities of Parametrized Quantum Circuits for Functions in Sobolev Spaces
2025 Quantum article Computer Science Quantum Computing Algorithms and Architecture Open access

David Dechant, Jordi Tura, Vedran Dunjko

6

citations
Convergence of Gradient Descent for Recurrent Neural Networks: A Nonasymptotic Analysis
2025 SIAM Journal on Mathematics of Data Science article Computer Science Neural Networks and Applications Open access

Semih Çaycı, Atilla Eryılmaz

1

citations