Christian Igel

Christian Igel

Professor

ORCID: 0000-0003-2868-0856

Kommentarer til publikationsliste

This list of pubications is not fully complete.

For a complete list of older publications as well as papers and software available online please vist my old homepage: http://image.diku.dk/igel

I also maintain a Google Scholar profile: https://scholar.google.dk/citations?user=d-jF4zIAAAAJ


Udgivelsesår:
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  1. Udgivet

    Bi-modal Variational Autoencoders for Metabolite Identification Using Tandem Mass Spectrometry

    Kutuzova, S., Igel, Christian, Nielsen, Mads & McCloskey, D., 2021, bioRxiv, 22 s.

    Publikation: Working paper › Preprint › Forskning

  2. Udgivet

    Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote

    Wu, Yi Shan, Masegosa, A. R., Lorenzen, Stephan Sloth, Igel, Christian & Seldin, Yevgeny, 2021, Advances in Neural Information Processing Systems 34 (NeurIPS). NeurIPS Proceedings, s. 1-12

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  3. Udgivet

    Data, Knowledge, and Computation

    Igel, Christian, 2021, I: KI - Kunstliche Intelligenz. 35, s. 247–249

    Publikation: Bidrag til tidsskrift › Leder › Forskning

  4. Udgivet

    Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients

    Jimenez-Solem, E., Petersen, Tonny Studsgaard, Hansen, Casper, Hansen, Christian, Lioma, Christina, Igel, Christian, Boomsma, Wouter, Krause, Oswin, Lorenzen, Stephan Sloth, Selvan, Raghav, Petersen, Janne, Nyeland, M. E., Ankarfeldt, Mikkel Zöllner, Virenfeldt, G. M., Winther-Jensen, M., Linneberg, Allan René, Mehdipour Ghazi, Mostafa, Detlefsen, N., Lauritzen, Andreas, Smith, Abraham George, de Bruijne, Marleen, Ibragimov, Bulat, Petersen, Jens, Lillholm, Martin, Middleton, Jon Anthony, Mogensen, S. H., Thorsen-Meyer, H., Perner, Anders, Helleberg, M., Kaas-Hansen, Benjamin Skov, Bonde, M., Bonde, A., Pai, A., Nielsen, Mads & Sillesen, Martin Hylleholt, 2021, I: Scientific Reports. 11, 1, 12 s., 3246.

    Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

  5. Udgivet

    Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

    Jørgensen, R. K. & Igel, Christian, 2021, I: Intelligent Systems in Accounting, Finance and Management. 28, 3, s. 159-172

    Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

  6. Udgivet

    On scaling contrastive representations for low-resource speech recognition

    Borgholt, L., Tax, T. M. S., Havtorn, J. D., Maaløe, L. & Igel, Christian, 2021, ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Bind 2021-June. s. 3885-3889

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  7. Udgivet

    On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions.

    Brügge, K., Fischer, A. & Igel, Christian, 2021, Proceedings of The 24th International Conference on Artificial Intelligence and Statistic. PMLR, s. 469-477 (Proceedings of Machine Learning Research, Bind 130).

    Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt

  8. Udgivet

    The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset

    IWOAI Segmentation Challenge Writing Group, I. S. C. W. G., 2021, I: Radiology. Artificial intelligence. 3, 3, 13 s., e200078.

    Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

  9. Udgivet

    U-Sleep: resilient high-frequency sleep staging

    Perslev, Mathias, Darkner, Sune, Kempfner, L., Nikolic, M., Jennum, Poul & Igel, Christian, 15 apr. 2021, I: npj Digital Medicine. 4, 1, 12 s., 72.

    Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

  10. Udgivet

    Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark

    Lorenzen, Stephan Sloth, Nielsen, Mads, Jimenez-Solem, E., Petersen, Tonny Studsgaard, Perner, Anders, Thorsen-Meyer, H., Igel, Christian & Sillesen, Martin Hylleholt, 23 sep. 2021, I: Scientific Reports. 11, 1, 10 s., 18959.

    Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

ID: 22657401