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Papers matching “deep neural network training” 58

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Post-Training Quantization for Energy Efficient Realization of Deep Neural Networks
2022 arXiv (Cornell University) preprint Computer Science Advanced Neural Network Applications Open access

Cecilia Latotzke, Batuhan Balim, Tobias Gemmeke

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
Stitching for Neuroevolution: Recombining Deep Neural Networks without Breaking Them
2024 arXiv (Cornell University) preprint Computer Science Evolutionary Algorithms and Applications Open access

Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman

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
Rethinking Evaluation Paradigms in IBP-based Certified Training
2026 arXiv (Cornell University) preprint Computer Science Adversarial Robustness in Machine Learning Open access

Konstantin Kaulen, Hadar Shavit, Holger H. Hoos

0

citations
Criticality versus uniformity in deep neural networks
2023 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Aleksandar Bukva, Jurriaan de Gier, Kevin T. Grosvenor, Ro Jefferson, Koenraad Schalm, Eliot Schwander

5

citations
Speed Limits for Deep Learning
2023 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Inbar Seroussi, Alexander A. Alemi, Moritz Helias, Zohar Ringel

0

citations
Preprint: Norm Loss: An efficient yet effective regularization method for deep neural networks
2021 arXiv (Cornell University) preprint Computer Science Advanced Neural Network Applications Open access

Sebastian Schmitt, Thomas Bäck, Wei Chen, Michael S. Lew

1

citations
Efficient EEG Seizure Detection Using INT8 Quantization, Channel Pruning, and Spiking Neural Networks
2026 arXiv (Cornell University) preprint Computer Science Advanced Neural Network Applications Open access

Kartikey Ahlawat

0

citations
Assessing the performance of implicit ensembling of neural networks for proteochemometric modeling with RandomNets
2026 ChemRxiv preprint Computer Science Computational Drug Discovery Methods

Chiel Jespers, Olivier J. M. Béquignon, Mike Preuß, Gerard J. P. van Westen

0

citations
Robust Communication and Computation using Deep Learning via Joint Uncertainty Injection
2024 arXiv (Cornell University) preprint Computer Science IoT and Edge/Fog Computing Open access

Robert-Jeron Reifert, Hayssam Dahrouj, Alaa Alameer Ahmad, Haris Gacanin, Aydin Sezgin

0

citations
Interpreting Emergent Features in Deep Learning-based Side-channel Analysis
2025 arXiv (Cornell University) preprint Computer Science Cryptographic Implementations and Security Open access

Sengim Karayalçın, Marina Krček, Stjepan Picek

0

citations
Superpixel segmentations for thin sections: evaluation of methods to enable the generation of machine learning training data sets
2021 preprint Computer Science Advanced Neural Network Applications Open access

Jiaxin Yu, Florian Wellmann, Simon Virgo, Marven von Domarus, Mingze Jiang, Joyce Schmatz, +1 more

2

citations
Adversarial Examples on Object Recognition: A Comprehensive Survey
2020 arXiv (Cornell University) preprint Computer Science Adversarial Robustness in Machine Learning Open access

Alex Serban, Erik Poll, Joost Visser

11

citations
A Mean-Field Theory of Transformers: Well-Posedness of the Coupled Data--Parameter Dynamics and Global Convergence of Training
2026 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Michael Herty, Hailiang Liu

0

citations
Multi-Objective Learning for Deformable Image Registration
2024 arXiv (Cornell University) preprint Computer Science Medical Image Segmentation Techniques Open access

Monika Grewal, Henrike G. Westerveld, Peter A. N. Bosman, Tanja Alderliesten

0

citations
Continuous limits of residual neural networks in case of large input data
2021 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Michael Herty, A. Thuenen, T. Trimborn, G. Visconti

1

citations
Prediction of heart transplant rejection from routine pathology slides with self-supervised Deep Learning
2022 medRxiv preprint Computer Science AI in cancer detection Open access

Tobias Paul Seraphin, Mark Luedde, Christoph Roderburg, Marko van Treeck, Pascal Scheider, Roman David Buelow, +11 more

4

citations
Hidden Variables in Deep Learning Digital Pathology and Their Potential to Cause Batch Effects: Prediction Model Study (Preprint)
2020 preprint Computer Science AI in cancer detection Open access

Max Schmitt, Roman Christoph Maron, Achim Hekler, Albrecht Stenzinger, Axel Hauschild, Michael Weichenthal, +11 more

0

citations
Convergence of gradient descent for learning linear neural networks
2021 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Gabin Maxime Nguegnang, Holger Rauhut, Ulrich Terstiege

1

citations
Subcortical Segmentation of the Fetal Brain in 3D Ultrasound using Deep Learning
2021 bioRxiv (Cold Spring Harbor Laboratory) preprint Computer Science Medical Image Segmentation Techniques Open access

Linde S. Hesse, Moska Aliasi, Felipe A. Moser, Monique C. Haak, Weidi Xie, Mark Jenkinson, +1 more

4

citations
Data-Driven Qubit Characterization and Optimal Control using Deep Learning
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Paul Surrey, Julian D. Teske, Tobias Hangleiter, Hendrik Bluhm, Pascal Cerfontaine

0

citations
Data-Driven Qubit Characterization and Optimal Control using Deep Learning
2026 arXiv (Cornell University) preprint Computer Science Quantum Computing Algorithms and Architecture Open access

Paul Surrey, Julian D. Teske, Tobias Hangleiter, Hendrik Bluhm, Pascal Cerfontaine

0

citations
Deep Learning Approach for Bubble Detection and Segmentation with YOLOv5
2024 Preprints.org preprint Computer Science Advanced Neural Network Applications Open access

Amit Sharma, Moritz Eickhoff, Thomas Echterhof, Christian Wuppermann

6

citations
Graph Neural Networks Do Not Always Oversmooth
2024 arXiv (Cornell University) preprint Computer Science Advanced Graph Neural Networks Open access

Bastian Epping, Alexandre René, Moritz Helias, Michael T. Schaub

3

citations