Oswin Krause

Oswin Krause

Assistant Professor, Tenure Track Assistant Professor


  1. 2020
  2. Published

    Algorithms for estimating the partition function of restricted Boltzmann machines

    Krause, Oswin, Fischer, A. & Igel, Christian, Jan 2020, In: Artificial Intelligence. 278, 19 p., 103195.

    Research output: Contribution to journalJournal articlepeer-review

  3. Published

    A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model

    Czolbe, Steffen, Krause, Oswin, Cox, Ingemar Johansson & Igel, Christian, 2020, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtua. NeurIPS Proceedings, (Advances in Neural Information Processing Systems, Vol. 33).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  4. Published

    Algorithms for estimating the partition function of restricted Boltzmann machines: (Extended Abstract)

    Krause, Oswin, Fischer, A. & Igel, Christian, 2020, Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020. Bessiere, C. (ed.). International Joint Conferences on Artificial Intelligence, p. 5045-5049 5 p. (IJCAI International Joint Conference on Artificial Intelligence, Vol. 2021-January).

    Research output: Chapter in Book/Report/Conference proceedingConference abstract in proceedingsResearchpeer-review

  5. Published

    Bayesian active learning for maximal information gain on model parameters

    Arnavaz, Kasra, Feragen, A., Krause, Oswin & Loog, M., 2020, Proceedings of ICPR 2020 - 25th International Conference on Pattern Recognition. IEEE, p. 10524-10531 8 p. 9411962

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

  6. Published

    The hessian estimation evolution strategy

    Glasmachers, T. & Krause, Oswin, 2020, Parallel Problem Solving from Nature – PPSN XVI - 16th International Conference, PPSN 2020, Proceedings. Bäck, T., Preuss, M., Deutz, A., Emmerich, M., Wang, H., Doerr, C. & Trautmann, H. (eds.). Springer, p. 597-609 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12269 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

ID: 40813873