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Deep conditional generative models

2022/45/B/ST6/01117

Keywords

Descriptors

  • ST6_011: Uczenie maszynowe, statystyczne przetwarzanie danych i zastosowania w przetwarzaniu sygnałów (np. mowy, obrazów, filmów)

Panel

ST6 – Computer science and informatics: informatics and information systems, computer science, scientific computing, intelligent systems

Host institution

Uniwersytet Jagielloński, Wydział Matematyki i Informatyki

Voivodeship: małopolskie

Other projects carried out by the institution »

Principal investigator (from the host institution)

dr Marek Śmieja

Number of co-investigators in the project: 5

Call

OPUS 23 – announced on 2022-03-28

Amount awarded
668 932 PLN
Project start date
2023-01-11
Project end date
2026-04-10
Project duration
39 months (the same as in the proposal)
Project status
Project completed

Project description

Download the project description in a pdf file

Note — project descriptions were prepared by the authors of the applications themselves and placed in the system in an unchanged form.

Information in the final report

Publication in academic press/journals (2)

  1. Multi-Label Conditional Generation from Pre-trained Models

    Authors:
    M. Proszewska, M. Wołczyk, M. Zieba, P. Wielopolski, Ł. Maziarka and M. Śmieja
    Academic press:
    IEEE Transactions on Pattern Analysis and Machine Intelligence (year: 2024, volume: 46/9, pages: 6185-6198), Publisher: IEEE
    Status:
    Published
    DOI:
    10.1109/TPAMI.2024.3382008 – link to the publication

  2. Augmentation-aware Self-supervised Learning with Conditioned Projector

    Authors:
    Marcin Przewięźlikowski, Mateusz Pyla, Bartosz Zieliński ,Bartłomiej Twardowski ,Jacek Tabor, Marek Śmieja
    Academic press:
    Knowledge-Based Systems (year: 2024, volume: 205, pages: 112572), Publisher: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.knosys.2024.112572 – link to the publication

Articles in post-conference publications (9)

  1. StyleAutoEncoder for manipulating image attributes using pre-trained StyleGAN

    Authors:
    Bedychaj, A.; Tabor, J.; and Śmieja, M.
    Conference:
    Advances in Knowledge Discovery and Data Mining (year: 2024, volume: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pages: 118--130), Publisher: Springer
    Date:
    conference 2024-05-07 - 2024-05-10
    Status:
    Published
    DOI:
    10.1007/978-981-97-2253-2_10 – link to the publication

  2. Face Identity-Aware Disentanglement in StyleGAN

    Authors:
    Suwała, A.; Wójcik, B.; Proszewska, M.; Tabor, J.; Spurek, P.; and Śmieja, M.
    Conference:
    IEEE/CVF Winter Conference on Applications of Computer Vision (year: 2024, volume: IEEE/CVF Winter Conference on Applications of Computer Vision, pages: 5222–5231), Publisher: Computer Vision Foundation
    Date:
    conference 2024-01-04 - 2024-01-08
    Status:
    Published
    DOI:
    10.1109/WACV57701.2024.00514 – link to the publication

  3. RGFN: Synthesizable Molecular Generation Using GFlowNets

    Authors:
    Michał Koziarski, Andrei Rekesh, Dmytro Shevchuk, Almer van der Sloot, Piotr Gaiński, Yoshua Bengio, Chenghao Liu, Mike Tyers, Robert Batey
    Conference:
    Advances in Neural Information Processing Systems (year: 2024, volume: NeurIPS Neural Information Processing, pages: 46908-46955), Publisher: MIT Press
    Date:
    conference 2024-12-10 - 2024-12-15
    Status:
    Published
    DOI:
    link to the publication

  4. A deep cut into Split Federated Self-Supervised Learning

    Authors:
    Przewięźlikowski, M.; Osial, M.; Śmieja, M.; and Zielinski
    Conference:
    Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2024. Lecture Notes in Computer Science(), vol 14942 (year: 2024, volume: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages: 444–459), Publisher: Springer
    Date:
    conference 2024-09-09 - 2024-09-13
    Status:
    Published
    DOI:
    10.1007/978-3-031-70344-7_26 – link to the publication

  5. RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets

    Authors:
    Piotr Gaiński, Michał Koziarski, Krzysztof Maziarz, Marwin Segler, Jacek Tabor, Marek Śmieja
    Conference:
    ICLR Workshop on Generative and Experimental Perspectives for Biomolecular Design (year: 2024, volume: ICLR Workshop on Generative and Experimental Perspectives for Biomolecular Design, pages: 18), Publisher: openreview
    Date:
    conference 2024-05-07 - 2024-07-11
    Status:
    Published
    DOI:
    link to the publication

  6. ChiENN: Embracing Molecular Chirality with Graph Neural Networks

    Authors:
    Piotr Gaiński, Michał Koziarski, Jacek Tabor, Marek Śmieja
    Conference:
    Lecture Notes in Computer Science, vol. 14171 (year: 2023, volume: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages: 36–52), Publisher: Springer, Cham
    Date:
    conference 18-22 września 2023
    Status:
    Published
    DOI:
    10.1007/978-3-031-43418-1_3 – link to the publication

  7. r-softmax: Generalized Softmax with Controllable Sparsity Rate

    Authors:
    Klaudia Bałazy, Łukasz Struski, Marek Śmieja, Jacek Tabor
    Conference:
    Lecture Notes in Computer Science vol 14074 (year: 2013, volume: International Conference on Computational Science, pages: 137–145), Publisher: Springer, Cham
    Date:
    conference 3-5 lipiec 2023
    Status:
    Published
    DOI:
    10.1007/978-3-031-36021-3_11 – link to the publication

  8. Contrastive Hierarchical Clustering

    Authors:
    Michał Znalezniak, Przemysław Rola, Patryk Kaszuba, Jacek Tabor, Marek Śmieja
    Conference:
    Lecture Notes in Computer Science, vol 14169 (year: 2023, volume: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pages: 627–643), Publisher: Springer, Cham
    Date:
    conference 18-22 września 2023
    Status:
    Published
    DOI:
    10.1007/978-3-031-43412-9_37 – link to the publication

  9. HyperTab: Hypernetwork Approach for Deep Learning on Small Tabular Datasets

    Authors:
    Witold Wydmański, Oleksii Bulenok, Marek Śmieja
    Conference:
    2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA) (year: 2023, volume: IEEE 10th International Conference on Data Science and Advanced Analytics, pages: 9), Publisher: IEEE
    Date:
    conference 9-13 października 2023
    Status:
    Published
    DOI:
    10.1109/DSAA60987.2023.10302504 – link to the publication

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Graphic design and implementation: Jakub Piotrowski