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Papers matching “neural network generalization” 58

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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
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
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
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
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
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 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
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
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
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
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 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