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Papers matching “deep learning for inverse problems” 15

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Inverse deep learning raytracing for scalable heliostat surface prediction
2026 RWTH Publications (RWTH Aachen) dissertation Energy Solar Thermal and Photovoltaic Systems Open access

Jan Pascal Lewen

0

citations
Deep learning for size-agnostic inverse design of random-network 3D printed mechanical metamaterials
2022 arXiv (Cornell University) preprint Engineering Cellular and Composite Structures Open access

H. Pahlavani, Kostas Tsifoutis‐Kazolis, Prerak Mody, Jie Zhou, Mohammad Javad Mirzaali, AMIR ABBAS ZADPOOR

2

citations
Diffusion Based Unpaired Data Learning for Inverse Problems
2026 arXiv (Cornell University) preprint Computer Science Image and Signal Denoising Methods Open access

Chenglong Bao, Yiming Dang, Chenguang Duan, Yuling Jiao, Defeng Sun

0

citations
Deep Learning for Size‐Agnostic Inverse Design of Random‐Network 3D Printed Mechanical Metamaterials
2023 Advanced Materials article Engineering Cellular and Composite Structures Open access

H. Pahlavani, Kostas Tsifoutis‐Kazolis, Mauricio Cruz Saldívar, Prerak Mody, Jie Zhou, Mohammad Javad Mirzaali, +1 more

97

citations
Uncertainty quantification in machine learning: confidence intervals for high-dimensional regression
2025 RWTH Publications (RWTH Aachen) dissertation Engineering Sparse and Compressive Sensing Techniques Open access

Frederik Hoppe

0

citations
Noise2Inverse: Self-Supervised Deep Convolutional Denoising for Tomography
2020 IEEE Transactions on Computational Imaging article Computer Science Image and Signal Denoising Methods Open access

146

citations
ForwardFlow: Simulation only statistical inference using deep learning
2026 arXiv (Cornell University) preprint Mathematics Markov Chains and Monte Carlo Methods Open access

Stefan Böhringer

0

citations
Uncertainty Quantification For Learned ISTA
2023 IEEE International Workshop on Machine Learning for Signal Processing (MLSP) conference-paper Mathematics Numerical methods in inverse problems

Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Felix Krahmer, Holger Rauhut

4

citations
Uncertainty quantification for learned ISTA
2023 arXiv (Cornell University) preprint Engineering Sparse and Compressive Sensing Techniques Open access

Frederik Hoppe, Claudio Mayrink Verdun, Felix Krahmer, Hannah Laus, Holger Rauhut

0

citations
Deep neural-network based optimization for the design of a multi-element surface magnet for MRI applications
2022 Inverse Problems article Physics and Astronomy Model Reduction and Neural Networks Open access

Sumit Tewari, Sahar Yousefi, ANDREW G. WEBB

5

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
Shape analysis of training data for neural networks in Electrical Impedance Tomography
2023 Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society conference-paper Engineering Electrical and Bioimpedance Tomography

Jöran Rixen, Benedikt Eliasson, Simon Lyra, Steffen K. Leonhardt

0

citations
Deep Unrolled Networks in Representation Space Applied to MRI Reconstruction
2026 arXiv (Cornell University) preprint Medicine Advanced MRI Techniques and Applications Open access

Efe Ilıcak, Baris Imre, Chloé Najac, Ruben van den Broek, Beatrice Lena, Andrew Webb, +1 more

0

citations
A Novel Intrusion Detection Method Based on Lightweight Neural Network for Internet of Things
2021 IEEE Internet of Things Journal article Computer Science Network Security and Intrusion Detection

Ruijie Zhao, Guan Gui, Zhi Xue, Jie Yin, Tomoaki Otsuki Ohtsuki, Bamidele Adebisi, +1 more

225

citations
(Invited) Fundamentals of Thin Film Growth and Etching: How Small Atomic Processes Govern Macroscopic Effects
2023 ECS Meeting Abstracts conference-abstract Physics and Astronomy Surface and Thin Film Phenomena

Marcel J. Rost

0

citations

15 results