# Best Poster Award

The Best Poster Award is presented to the best poster presented on ML in PL Conference. The poster committee, composed of members of ML in PL Scientific Board and ML in PL Association, evaluates all posters on their scientific content, design, and clarity of the presentation by presenter.


Poster 16: Deep Neural Network Approach to Predict Properties of Drugs and Drug-Like Molecules
Magdalena Wiercioch (Jagiellonian University), Johannes Kirchmair (University of Vienna)


Poster 20: An efficient manifold density estimator for all recommendation systems
Adam Jakubowski (Synerise.com), Jacek Dąbrowski (Synerise.com), Barbara Rychalska (Synerise.com), Michał Daniluk (Synerise.com), Dominika Basaj (Synerise.com)

Poster 21: Universal Neural Vocoding and improving its expressiveness with non-affine Normalizing Flows
Adam Gabryś (Alexa AI), Yunlong Jiao (Alexa AI), Viacheslav Klimkov (Alexa AI), Daniel Korzekwa (Alexa AI)

# Best Poster Audience Award

The Best Poster Audience Award is presented to the best poster presented on ML in PL Conference according to the audience.


Poster 07: Guide through jungle of models! forester: An R package to automatically select between tree-based models
Anna Kozak (MI2DataLab, Warsaw University of Technology), Hoang Thien Ly (Warsaw University of Technology), Szymon Szmajdziński (Warsaw University of Technology), Przemysław Biecek (Warsaw University of Technology)


Poster 27: Mbaza - machine learning used in wildlife protection. Case study
Jędrzej Świeżewski (Appsilon)

# Best Contributed Talk Audience Award

The Best Contributed Talk Audience Award is presented to the best contributed talk presented on ML in PL Conference according to the audience.


Generative models in continual learning
Kamil Deja (Warsaw University of Technology), Wojciech Masarczyk (Warsaw University of Technology), Paweł Wawrzyński (Warsaw University of Technology), Tomasz Trzciński (Warsaw University of Technology)


Let's open the black box! Hessian-based toolbox for interpretable and reliable machines learning physics

Cell-counting in human embryo time-lapse monitoring
Piotr Wygocki (MIM Solutions & University of Warsaw), Michał Siennicki (MIM Solutions), Tomasz Gilewicz (MIM Solutions), Paweł Brysch (MIM Solutions)I w obu przypadkach

Deep learning for decoding 3D hand translation based on ECoG signal
Maciej Śliwowski (Univ. Grenoble Alpes), Matthieu Martin (Univ. Grenoble Alpes), Antoine Souloumiac (Université Paris-Saclay), Pierre Blanchart (Université Paris-Saclay), Tetiana Aksenova (Univ. Grenoble Alpes)