Projects funded by the NCN

Information on the principal investigator and host institution

Information of the project and the call

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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: Pending project

Project description

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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

  • Articles in post-conference publications (5)
  1. 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
  2. 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
  3. 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
  4. 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
  5. 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

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