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Papers matching “neural network generalization” 109

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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
Covered Forest: Fine-grained generalization analysis of graph neural networks
2024 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Ben Finkelshtein, Floris Geerts, Ron Levie

0

citations
Graph Neural Network-Based Multi-Agent Reinforcement Learning for Active Voltage Control: Performance and Topology Robustness
2025 SSRN Electronic Journal preprint Engineering Optimal Power Flow Distribution Open access

Chijioke Eze, Chetan Prakash, Antonello Monti

0

citations
Accelerating greenhouse gas retrievals with neural network-based forward models
2026 preprint Environmental Science Atmospheric and Environmental Gas Dynamics Open access

Fiona Lippert, Andrew Gerald Barr, Marcos Herreras-Giralda, Masahiro Momoi, Fernando Rejano, Sha Lu, +4 more

0

citations
Uncertainty-Aware Predictive Safety Filters for Probabilistic Neural Network Dynamics
2026 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Bernd Frauenknecht, Lukas Kesper, Daniel Mayfrank, Henrik Hose, Sebastian Trimpe

0

citations
ExPAN(N)D: Exploring Posits for Efficient Artificial Neural Network Design in FPGA-Based Systems
2020 arXiv (Cornell University) preprint Computer Science Numerical Methods and Algorithms Open access

Suresh Nambi, Salim Ullah, Siva Satyendra Sahoo, Aditya Lohana, Farhad Merchant, Akash S. Kumar

4

citations
Parameter-Adaptive Approximate MPC: Tuning Neural-Network Controllers without Retraining
2024 arXiv (Cornell University) preprint Engineering Advanced Control Systems Optimization Open access

Henrik Hose, Alexander Gräfe, Sebastian Trimpe

0

citations
Bridging brain and cognition: A multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners
2020 bioRxiv (Cold Spring Harbor Laboratory) preprint Psychology Cognitive Abilities and Testing Open access

Ivan L. Simpson-Kent, Eiko I. Fried, Danyal Akarca, Silvana Mareva, Edward Thomas Bullmore

5

citations
A physics-informed neural network approach to modelling elastoplastic soils and the implicit finite-element coupling
2024 preprint Engineering Geotechnical Engineering and Soil Mechanics Open access

Mingpeng Liu, Qinghua Zhang, Raúl Fuentes

1

citations
Does Compression Imply Generalization? A Minimum Description Length Perspective
2026 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Lincen Yang, Jiayang Shi, Nan Pu, Daniël M. Pelt, Matthijs van Leeuwen, Zhong Li, +1 more

0

citations
Compressive Sensing and Neural Networks from a Statistical Learning Perspective
2020 arXiv (Cornell University) preprint Engineering Sparse and Compressive Sensing Techniques Open access

Arash Behboodi, Holger Rauhut, Ekkehard Schnoor

1

citations
A Generalization Bound for a Family of Implicit Networks
2025 SSRN Electronic Journal preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Samy Wu Fung, Benjamin Berkels

0

citations
A Generalized Framework of Neural Networks for Hamiltonian Systems
2023 SSRN Electronic Journal preprint Physics and Astronomy Model Reduction and Neural Networks Open access

Philipp Horn, Veronica Saz Ulibarrena, Barry Koren, Simon Portegies Zwart

1

citations
REAP: Learning General Rearrangement Heuristics from Motion-Planner Feedback
2026 arXiv (Cornell University) preprint Computer Science AI-based Problem Solving and Planning Open access

Daniel Swoboda, Héctor Geffner

0

citations
Shifting-based Optimizable Linear Relaxations for General Activation Functions
2026 arXiv (Cornell University) preprint Computer Science Formal Methods in Verification Open access

Philipp Kern, László Antal, Erika Ábrahám, Carsten Sinz

0

citations
Intrinsic Dimension for Evaluating and Analyzing Neural Networks for Medical Image Segmentation
2025 SSRN Electronic Journal preprint Computer Science Medical Image Segmentation Techniques Open access

W. Li, Zeju Li, Jie Xu, Shichong Zhou, Yi Guo, Yuanyuan Wang

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
Discrete signaling mediates chaotic regularization in recurrent neural networks
2026 arXiv (Cornell University) preprint Neuroscience Neural dynamics and brain function Open access

Jan Bauer, Christian Keup, Jonathan Kadmon, Moritz Helias

0

citations
Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues
2026 arXiv (Cornell University) preprint Computer Science Gaussian Processes and Bayesian Inference Open access

Jakob Kramp, Javed Lindner, Moritz Helias

0

citations
Learning to Search and Searching to Learn for Generalization in Planning
2026 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Michael Aichmüller, Yannik Hesse, Hector Geffner

0

citations
Non-Asymptotic Analysis of Projected Gradient Descent for Physics-Informed Neural Networks
2025 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access

Jonas Nießen

0

citations
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
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