Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

Keywords

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Deep conditional generative models

2022/45/B/ST6/01117

Keywords:

deep learning generative models hypernetworks conditional distribution explainable AI generation of chemical compounds inverse problems

Descriptors:

  • ST6_011:

Panel:

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

Host institution :

Uniwersytet Jagielloński, Wydział Matematyki i Informatyki

woj. 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 (Y-m-d): 2023-01-11

Project end date (Y-m-d): 2026-01-10

Project duration:: 36 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)
  • Articles in post-conference publications (9)
  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 (rok: 2024, tom: 46/9, strony: 6185-6198), Wydawca: 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 (rok: 2024, tom: 205, strony: 112572), Wydawca: Elsevier
    Status:
    Published
    DOI:
    10.1016/j.knosys.2024.112572 - link to the publication
  1. 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 (rok: 2024, tom: NeurIPS Neural Information Processing, strony: 46908-46955), Wydawca: MIT Press
    Data:
    konferencja 2024-12-10 - 2024-12-15
    Status:
    Published
    DOI:
    link to the publication
  2. 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 (rok: 2024, tom: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, strony: 444–459), Wydawca: Springer
    Data:
    konferencja 2024-09-09 - 2024-09-13
    Status:
    Published
    DOI:
    10.1007/978-3-031-70344-7_26 - link to the publication
  3. Contrastive Hierarchical Clustering
    Authors:
    Michał Znalezniak, Przemysław Rola, Patryk Kaszuba, Jacek Tabor, Marek Śmieja
    Conference:
    Lecture Notes in Computer Science, vol 14169 (rok: 2023, tom: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, strony: 627–643), Wydawca: Springer, Cham
    Data:
    konferencja 18-22 września 2023
    Status:
    Published
    DOI:
    10.1007/978-3-031-43412-9_37 - link to the publication
  4. 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 (rok: 2023, tom: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, strony: 36–52), Wydawca: Springer, Cham
    Data:
    konferencja 18-22 września 2023
    Status:
    Published
    DOI:
    10.1007/978-3-031-43418-1_3 - link to the publication
  5. 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 (rok: 2013, tom: International Conference on Computational Science, strony: 137–145), Wydawca: Springer, Cham
    Data:
    konferencja 3-5 lipiec 2023
    Status:
    Published
    DOI:
    10.1007/978-3-031-36021-3_11 - link to the publication
  6. 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) (rok: 2023, tom: IEEE 10th International Conference on Data Science and Advanced Analytics, strony: 9), Wydawca: IEEE
    Data:
    konferencja 9-13 października 2023
    Status:
    Published
    DOI:
    10.1109/DSAA60987.2023.10302504 - link to the publication
  7. 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 (rok: 2024, tom: Pacific-Asia Conference on Knowledge Discovery and Data Mining, strony: 118--130), Wydawca: Springer
    Data:
    konferencja 2024-05-07 - 2024-05-10
    Status:
    Published
    DOI:
    10.1007/978-981-97-2253-2_10 - link to the publication
  8. 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 (rok: 2024, tom: IEEE/CVF Winter Conference on Applications of Computer Vision, strony: 5222–5231), Wydawca: Computer Vision Foundation
    Data:
    konferencja 2024-01-04 - 2024-01-08
    Status:
    Published
    DOI:
    10.1109/WACV57701.2024.00514 - link to the publication
  9. 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 (rok: 2024, tom: ICLR Workshop on Generative and Experimental Perspectives for Biomolecular Design, strony: 18), Wydawca: openreview
    Data:
    konferencja 2024-05-07 - 2024-07-11
    Status:
    Published
    DOI:
    link to the publication

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