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Papers matching “neural network generalization” 173

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Non-Asymptotic Optimization and Generalization Bounds for Stochastic Gauss-Newton in Overparameterized Models
2025 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Semih Çaycı

0

citations
A Generalization Bound for a Family of Implicit Networks
2024 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Samy Wu Fung, Benjamin Berkels

0

citations
Cross-Validation and Uncertainty Determination for Randomized Neural Networks with Applications to Mobile Sensors
2021 arXiv (Cornell University) preprint Computer Science Machine Learning and ELM Open access

Ansgar Steland, Bart Elger Pieters

1

citations
Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction
2022 RWTH Publications (RWTH Aachen) article Computer Science Computational Drug Discovery Methods Open access

Artur M. Schweidtmann, Jan G. Rittig, Jana M. Weber, Martin Grohe, Manuel Dahmen, Kai O. Leonhard, +1 more

3

citations
Query Languages for Neural Networks
2025 DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) article Computer Science Logic, Reasoning, and Knowledge Open access

Juno Steegmans

0

citations
Query Languages for Neural Networks
2024 arXiv (Cornell University) preprint Computer Science Logic, Reasoning, and Knowledge Open access

Martin Grohe, Christoph Standke, Juno Steegmans, Jan Van den Bussche

0

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
From Paintbrush to Pixel: A Review of Deep Neural Networks in AI-Generated Art
2026 Art & Perception article Computer Science Generative Adversarial Networks and Image Synthesis Open access

Anne-Sofie Maerten, Derya Soydaner

34

citations
Semi-Structured Distributional Regression -- Extending Structured Additive Models by Arbitrary Deep Neural Networks and Data Modalities
2020 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

David Rügamer, Chris Kolb, Nadja Klein

2

citations
MiniFool — Physics-Constraint-Aware Minimizer-Based Adversarial Attacks in Deep Neural Networks
2025 Research Square preprint Computer Science Adversarial Robustness in Machine Learning Open access

Lucie Flek, Oliver Janik, Akbar Karimi, Timo Saala, Alexander G. Schmidt, M. Schott, +4 more

0

citations
Fast and Flexible Spiking Network Simulations on Massively Distributed On-Chip Memory Accelerators
2026 arXiv (Cornell University) preprint Computer Science Parallel Computing and Optimization Techniques Open access

Catherine Mia Schöfmann, Jan Finkbeiner, Jan Vogelsang, Susanne Kunkel

0

citations
Learning General Policies with Policy Gradient Methods
2023 conference-paper Computer Science Reinforcement Learning in Robotics Open access

Simon Ståhlberg, Blai Bonet, Héctor Geffner

10

citations
Learning General Policies with Policy Gradient Methods
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Learning General Policies with Policy Gradient Methods
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Symmetries and Expressive Requirements for Learning General Policies
2024 conference-paper Computer Science AI-based Problem Solving and Planning Open access

Dominik Drexler, Simon Ståhlberg, Blai Bonet, Héctor Geffner

1

citations
Symmetries and Expressive Requirements for Learning General Policies
2024 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Dominik Drexler, Simon Ståhlberg, Blai Bonet, Héctor Geffner

0

citations
Efficient Lookahead Encoding and Abstracted Width for Learning General Policies in Classical Planning
2026 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Michael Aichmüller, Simon Ståhlberg, Martin Funkquist, Hector Geffner

0

citations
Towards General Negotiation Strategies with End-to-End Reinforcement Learning
2024 arXiv (Cornell University) preprint Computer Science Multi-Agent Systems and Negotiation Open access

Bram M. Renting, Thomas M. Moerland, Holger H. Hoos, Catholijn M. Jonker

0

citations
ImageGrains 2.0: Improved precision and generalization for grain segmentation
2026 preprint Computer Science Advanced Neural Network Applications Open access

David Mair, Guillaume Witz, Ariel Do Prado, Philippos Garefalakis, Amanda Wild, Fanny Ville, +8 more

0

citations
ImageGrains 2.0: Improved precision and generalization for grain segmentation
2026 Earth Surface Dynamics article Computer Science Advanced Neural Network Applications Open access

David Mair, Guillaume Witz, Ariel Do Prado, Philippos Garefalakis, Amanda Wild, Fanny Ville, +9 more

0

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, Michael Krämer, +1 more

0

citations
Mask R-CNN based droplet detection in liquid–liquid systems, Part 3: Model generalization for accurate processing performance independent of image quality
2023 Process Safety and Environmental Protection article Computer Science Advanced Neural Network Applications

Stepan Sibirtsev, Song Zhai, Andreas Jupke

13

citations
Overparameterization and generalization error: weighted trigonometric interpolation
2020 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Yuege Xie, Hung-Hsu Chou, Holger Rauhut, Rachel Ward

0

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