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Papers matching “deep learning training” 417

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CHEQ-ing the Box: Safe Variable Impedance Learning for Robotic Polishing
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Emma Cramer, Lukas Jäschke, Sebastian Trimpe

0

citations
Upside Down Reinforcement Learning with Policy Generators
2025 arXiv (Cornell University) preprint Computer Science Reinforcement Learning in Robotics Open access

Dylan R. Ashley, Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber

1

citations
ROSAR: An Adversarial Re-Training Framework for Robust Side-Scan Sonar Object Detection
2024 arXiv (Cornell University) preprint Computer Science Adversarial Robustness in Machine Learning Open access

Martin Aubard, László Antal, Ana Maria Madureira, Luís Filipe Teixeira, Erika Ábrahám

0

citations
QS4D: Quantization‐Aware Training for Efficient Hardware Deployment of Structured State‐Space Sequential Models
2026 Advanced Intelligent Systems article Computer Science Advanced Neural Network Applications Open access

Sebastian Siegel, Ming-Jay Yang, Younes Bouhadjar, Maxime Fabre, Emre Neftci, John Paul Strachan

1

citations
What Should a Network-Aware Agent Observe? A Systematic Analysis of Metadata Features for Reinforcement Learning Control over Wireless Links
2026 Electronics article Computer Science Reinforcement Learning in Robotics Open access

André Gilerson, Robert Heinrich Schmitt

0

citations
Gradient Descent for Deep Matrix Factorization: Dynamics and Implicit Bias towards Low Rank
2020 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Hung-Hsu Chou, Carsten Gieshoff, Johannes Maly, Holger Rauhut

2

citations
Uncertainty-Aware Federated Learning for Joint Communication and Computation in XR Systems
2026 IEEE Transactions on Mobile Computing article Computer Science Privacy-Preserving Technologies in Data Open access

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

0

citations
A dataset of insect sounds from 459 species for bioacoustic machine learning
2026 Scientific Data data-paper Computer Science Music and Audio Processing Open access

Marius Faiß, Burooj Ghani, Dan Stowell

6

citations
Learning General Policies from Examples
2025 Principles of Knowledge Representation and Reasoning conference-paper Computer Science AI-based Problem Solving and Planning Open access

Blai Bonet, Héctor Geffner

0

citations
AblationNet: Deep network for ablation zone segmentation, in hepatic CT, using Fourier contours
2026 Biomedical Signal Processing and Control article Computer Science Medical Image Segmentation Techniques Open access

Faeze Gholamiankhah, Gonnie C. M. van Erp, Alexander Broersen, Silvia L. Pintea, Coosje A. M. Verhagen, Pim Hendriks, +2 more

1

citations
Einsparung kostenintensiver Experimente und Simulationen durch Maschinelles Lernen
2021 Springer eBooks book-chapter Computer Science Neural Networks and Applications

Michaël Herty, Michael Rom, Giuseppe Visconti

6

citations
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms
2024 SIAM Journal on Scientific Computing article Computer Science Neural Networks and Applications

Danimir T. Doncevic, Alexander Mitsos, Y. P. Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, +1 more

9

citations
Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play?
2020 arXiv (Cornell University) preprint Computer Science Artificial Intelligence in Games Open access

Hui Wang, Michael Emmerich, Mike Preuß, Aske Plaat

2

citations
Convergence rates of deep ReLU networks for multiclass classification
2022 Electronic Journal of Statistics article Computer Science Stochastic Gradient Optimization Techniques Open access

Thijs Bos, Johannes Schmidt-Hieber

21

citations
Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation
2023 preprint Computer Science Medical Image Segmentation Techniques Open access

Prerak Mody

0

citations
Convergence rates of deep ReLU networks for multiclass classification
2021 arXiv (Cornell University) preprint Computer Science Stochastic Gradient Optimization Techniques Open access

Thijs Bos, Johannes Schmidt-Hieber

0

citations
Abstract LB114: Improved breast cancer prognostication through multimodal fusion of H&E and RNA FISH imaging
2025 Cancer Research conference-abstract Computer Science AI in cancer detection

Firas Khader, Daniel Truhn, Pavol Čekan, Evan David Paul, Jakob Nikolas Kather, Omar S. M. El Nahhas

1

citations
Development of AI-based pathology biomarkers in gastrointestinal and liver cancer
2020 Nature Reviews Gastroenterology & Hepatology article Computer Science AI in cancer detection

Jakob Nikolas Kather, Julien Caldéraro

81

citations
Building a Digital Health Twin for Personalized Intervention: The EPI Project
2020 arXiv (Cornell University) preprint Computer Science Privacy-Preserving Technologies in Data Open access

40

citations
Large-Scale Modeling of Sparse Protein Kinase Activity Data
2023 Journal of Chemical Information and Modeling article Computer Science Computational Drug Discovery Methods Open access

Sohvi Luukkonen, Erik Meijer, Giovanni A. Tricarico, Johan Hofmans, Pieter F. W. Stouten, Gerard J. P. van Westen, +1 more

14

citations
Large-scale modelling of sparse kinase activitydata
2023 ChemRxiv preprint Computer Science Computational Drug Discovery Methods Open access

Sohvi Luukkonen, Erik Meijer, Giovanni A. Tricarico, Johan Hofmans, Pieter F. W. Stouten, Gerard J. P. van Westen, +1 more

0

citations
Autoencoder-enabled model portability for reducing hyperparameter tuning efforts in side-channel analysis
2023 Journal of Cryptographic Engineering article Computer Science Cryptographic Implementations and Security Open access

Marina Krček, Guilherme Perin

5

citations
$μ$PC: Scaling Predictive Coding to 100+ Layer Networks
2025 arXiv (Cornell University) preprint Computer Science Neural Networks and Applications Open access

Francesco Innocenti, El Mehdi Achour, Christopher L. Buckley

0

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

Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias

4

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