Signals, Waves, and Learning: A Data-Driven Paradigm for Wave-Based Inverse Problems

Project Information

SWING

Grant agreement ID: 852821

DOI

10.3030/852821

Project closed

EC signature date 30 October 2019

Start date 1 January 2020

End date 31 December 2024

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 986 430,00

EU contribution

€ 1 986 430,00

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Other (8)

Neural equilibria for long-term prediction of nonlinear conservation laws

Author(s): J. Antonio Lara Benitez, Junyi Guo, Kareem Hegazy, Ivan Dokmanić, Michael W. Mahoney, Maarten V. de Hoop
Published in: 2025
Publisher: arXiv
DOI: 10.48550/arxiv.2501.06933

Conditional Injective Flows for Bayesian Imaging

Author(s): AmirEhsan Khorashadizadeh, Konik Kothari, Leonardo Salsi, Ali Aghababaei Harandi, Maarten de Hoop, Ivan Dokmanić
Published in: 2022
Publisher: NA

A spring-block theory of feature learning in deep neural networks

Author(s): Cheng Shi, Liming Pan, Ivan Dokmanić
Published in: 2024
Publisher: arXiv

An Approximation Theory for Metric Space-Valued Functions With A View Towards Deep Learning

Author(s): Kratsios, Anastasis; Liu, Chong; Lassas, Matti; de Hoop, Maarten V.; Dokmanić, Ivan
Published in: Issue 4, 2023
Publisher: arXiv
DOI: 10.48550/arxiv.2304.12231

LoFi: Neural Local Fields for Scalable Image Reconstruction

Author(s): AmirEhsan Khorashadizadeh, Tobías I. Liaudat, Tianlin Liu, Jason D. McEwen, Ivan Dokmanić
Published in: 2024
Publisher: arXiv

End-to-end localized deep learning for Cryo-ET

Author(s): Vinith Kishore, Valentin Debarnot, Ricardo D. Righetto, AmirEhsan Khorashadizadeh, Ivan Dokmanić
Published in: 2025
Publisher: arXiv
DOI: 10.48550/arxiv.2501.15246

Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown-View Tomography

Author(s): Shuai Huang, Mona Zehni, Ivan Dokmanic, Zhizhen Zhao
Published in: arXiv, 2022
Publisher: NA

High-Rate Phase Association with Travel Time Neural Fields

Author(s): Cheng Shi, Giulio Poggiali, Chris Marone, Maarten V. de Hoop, Ivan Dokmanić
Published in: 2024
Publisher: arXiv
DOI: 10.48550/arxiv.2307.07572

Peer reviewed articles (16)

Total Least Squares Phase Retrieval

Author(s): Sidharth Gupta, Ivan Dokmanic
Published in: IEEE Transactions on Signal Processing, Issue 70, 2024, Page(s) 536-549, ISSN 1053-587X
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tsp.2021.3128750

Ice-Tide: Implicit Cryo-ET Imaging and Deformation Estimation

Author(s): Valentin Debarnot, Vinith Kishore, Ricardo D. Righetto, Ivan Dokmanić
Published in: IEEE Transactions on Computational Imaging, Issue 11, 2025, Page(s) 24-35, ISSN 2333-9403
Publisher: IEEE
DOI: 10.1109/tci.2024.3519805

Differentiable Uncalibrated Imaging

Author(s): Sidharth Gupta, Konik Kothari, Valentin Debarnot, Ivan Dokmanić
Published in: IEEE Transactions on Computational Imaging, Issue 10, 2024, Page(s) 1-16, ISSN 2333-9403
Publisher: IEEE
DOI: 10.1109/tci.2023.3346294

Deep Injective Prior for Inverse Scattering

Author(s): AmirEhsan Khorashadizadeh, Vahid Khorashadizadeh, Sepehr Eskandari, Guy A. E. Vandenbosch, Ivan Dokmanić
Published in: IEEE Transactions on Antennas and Propagation, Issue 71, 2023, Page(s) 8894-8906, ISSN 0018-926X
Publisher: Institute of Electrical and Electronics Engineers
DOI: 10.1109/tap.2023.3312818

Conditional Injective Flows for Bayesian Imaging

Author(s): AmirEhsan Khorashadizadeh, Konik Kothari, Leonardo Salsi, Ali Aghababaei Harandi, Maarten de Hoop, Ivan Dokmanić
Published in: IEEE Transactions on Computational Imaging, Issue 9, 2024, Page(s) 224-237, ISSN 2333-9403
Publisher: IEEE
DOI: 10.1109/tci.2023.3248949

Injectivity of ReLU networks: Perspectives from statistical physics

Author(s): Antoine Maillard, Afonso S. Bandeira, David Belius, Ivan Dokmanić, Shuta Nakajima
Published in: Applied and Computational Harmonic Analysis, Issue 76, 2025, Page(s) 101736, ISSN 1063-5203
Publisher: Academic Press
DOI: 10.1016/j.acha.2024.101736

Learning Multiscale Convolutional Dictionaries for Image Reconstruction

Author(s): Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanić
Published in: IEEE Transactions on Computational Imaging, 2022, ISSN 2333-9403
Publisher: IEEE

WaveBench: Benchmarking Data-driven Solvers for Linear Wave Propagation PDEs

Author(s): Liu, Tianlin; Lara Benitez, Jose Antonio; Faucher, Florian; Khorashadizadeh, Amirehsan; de Hoop, Maarten; Dokmanić, Ivan
Published in: Transactions on Machine Learning Research Journal, Issue 1, 2024, ISSN 2835-8856
Publisher: OpenReview.net

Homophily modulates double descent generalization in graph convolution networks

Author(s): Cheng Shi, Liming Pan, Hong Hu, Ivan Dokmanić
Published in: Proceedings of the National Academy of Sciences, Issue 121, 2024, ISSN 0027-8424
Publisher: National Academy of Sciences
DOI: 10.1073/pnas.2309504121

Learning sub-patterns in piecewise continuous functions

Author(s): Kratsios, Anastasis; Zamanlooy, Behnoosh
Published in: Neurocomputing, Issue 09252312, 2022, ISSN 0925-2312
Publisher: Elsevier BV
DOI: 10.1016/j.neucom.2022.01.036

Orthogonal Matrix Retrieval with Spatial Consensus for 3D Unknown View Tomography

Author(s): Shuai Huang, Mona Zehni, Ivan Dokmanić, Zhizhen Zhao
Published in: SIAM Journal on Imaging Sciences, Issue 16, 2024, Page(s) 1398-1439, ISSN 1936-4954
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/22m1498218

Globally Injective ReLU Networks

Author(s): Michael Puthawala, Konik Kothari, Matti Lassas, Ivan Dokmanić, Maarten de Hoop
Published in: Journal of Machine Learning Research, 2022, ISSN 1532-4435
Publisher: MIT Press

Learning Multiscale Convolutional Dictionaries for Image Reconstruction

Author(s): Tianlin Liu, Anadi Chaman, David Belius, Ivan Dokmanic
Published in: IEEE Transactions on Computational Imaging, Issue 8, 2022, Page(s) 425-437, ISSN 2333-9403
Publisher: IEEE
DOI: 10.1109/tci.2022.3175309

Total Least Squares Phase Retrieval

Author(s): Sidharth Gupta, Ivan Dokmanić
Published in: IEEE Transactions on Signal Processing, 2021, ISSN 1941-0476
Publisher: IEEE

A Graph Dynamics Prior for Relational Inference

Author(s): Liming Pan, Cheng Shi, Ivan Dokmanic
Published in: Proceedings of the AAAI Conference on Artificial Intelligence, Issue 38, 2024, Page(s) 14508-14516, ISSN 2374-3468
Publisher: AAAI Press
DOI: 10.1609/aaai.v38i13.29366

Designing universal causal deep learning models: The geometric (Hyper)transformer

Author(s): Beatrice Acciaio, Anastasis Kratsios, Gudmund Pammer
Published in: Mathematical Finance, Issue 34, 2024, Page(s) 671-735, ISSN 0960-1627
Publisher: Blackwell Publishing Inc.
DOI: 10.1111/mafi.12389

Conference proceedings (14)

Truly shift-invariant convolutional neural networks

Author(s): Anadi Chaman, Ivan Dokmanic
Published in: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023, Page(s) 3772-3782
Publisher: IEEE
DOI: 10.1109/cvpr46437.2021.00377

Universal Joint Approximation of Manifolds and Densities by Simple Injective Flows

Author(s): Michael Puthawala, Matti Lassas, Ivan Dokmanic, Maarten De Hoop
Published in: Proceedings of the 39th International Conference on Machine Learning, 2022
Publisher: PMLR

Joint Graph Rewiring and Feature Denoising via Spectral Resonance

Author(s): Jonas Linkerhägner, Cheng Shi, Ivan Dokmanić
Published in: The Thirteenth International Conference on Learning Representations (ICLR), 2025
Publisher: OpenReview.net
DOI: 10.48550/arxiv.2408.07191

Deep Variational Inverse Scattering : (Invited Paper)

Author(s): AmirEhsan Khorashadizadeh, Ali Aghababaei, Tin Vlašić, Hieu Nguyen, Ivan Dokmanić
Published in: 2023 17th European Conference on Antennas and Propagation (EuCAP), 2024, Page(s) 1-5
Publisher: IEEE
DOI: 10.23919/eucap57121.2023.10133365

Neural Link Prediction with Walk Pooling

Author(s): Liming Pan, Cheng Shi, Ivan Dokmanic
Published in: International Conference on Learning Representations, 2022
Publisher: Tenth International Conference on Learning Representations

Universal Approximation Under Constraints is Possible with Transformers

Author(s): Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanic
Published in: International Conference on Learning Representations, 2022
Publisher: ICLR

Truly Shift-Invariant Convolutional Neural Networks

Author(s): Anadi Chaman, Ivan Dokmanic
Published in: IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021
Publisher: IEEE

Trumpets: Injective Flows for Inference and Inverse Problems

Author(s): Kothari, Konik; Khorashadizadeh, AmirEhsan; de Hoop, Maarten; Dokmanić, Ivan
Published in: Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Publisher: NA

Implicit Neural Representation for Mesh-Free Inverse Obstacle Scattering

Author(s): Tin Vlašić, Hieu Nguyen, Ivan Dokmanić
Published in: Asilomar Conference on Signals, Systems, and Computers, 2022
Publisher: NA

Truly shift-equivariant convolutional neural networks with adaptive polyphase upsampling

Author(s): Anadi Chaman, Ivan Dokmanić
Published in: 2021 55th Asilomar Conference on Signals, Systems, and Computers, 2021
Publisher: IEEE

Manifold Rewiring for Unlabeled Imaging

Author(s): Valentin Debarnot, Vinith Kishore, Cheng Shi, Ivan Dokmanic
Published in: APSIPA, 2022
Publisher: IEEE

Joint Cryo-ET Alignment and Reconstruction with Neural Deformation Fields

Author(s): Valentin Debarnot, Sidharth Gupta, Konik Kothari, Ivan Dokmanić
Published in: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024, Page(s) 1-5
Publisher: IEEE
DOI: 10.1109/icassp49357.2023.10095454

Learning the Geometry of Wave-Based Imaging

Author(s): Konik Kothari, Maarten de Hoop, Ivan Dokmanić
Published in: Advances in Neural Information Processing Systems, Issue 33, 2020
Publisher: Advances in Neural Information Processing Systems

SeisLM: a Foundation Model for Seismic Waveforms

Author(s): Tianlin Liu, Jannes Münchmeyer, Laura Laurenti, Chris Marone, Maarten V. de Hoop, Ivan Dokmanić
Published in: NeurIPS 2024 workshop on Foundation Models for Science: Progress, Opportunities, and Challenges, 2024
Publisher: NA