Marek Śmieja

About Marek Śmieja

Marek Śmieja, With an exceptional h-index of 15 and a recent h-index of 13 (since 2020), a distinguished researcher at Uniwersytet Jagiellonski, specializes in the field of semi-supervised learning, learning from missing data, deep learning, clustering, cheminformatics.

His recent articles reflect a diverse array of research interests and contributions to the field:

StyleAutoEncoder for Manipulating Image Attributes Using Pre-trained StyleGAN

Multi-Label Conditional Generation From Pre-Trained Models

ADMET-PrInt: Evaluation of ADMET Properties: Prediction and Interpretation

Face Identity-Aware Disentanglement in StyleGAN

Hypertab: Hypernetwork approach for deep learning on small tabular datasets

ChiENN: Embracing Molecular Chirality with Graph Neural Networks

r-softmax: Generalized Softmax with Controllable Sparsity Rate

Augmentation-aware self-supervised learning with guided projector

Marek Śmieja Information

University

Position

___

Citations(all)

714

Citations(since 2020)

625

Cited By

246

hIndex(all)

15

hIndex(since 2020)

13

i10Index(all)

20

i10Index(since 2020)

15

Email

University Profile Page

Google Scholar

Marek Śmieja Skills & Research Interests

semi-supervised learning

learning from missing data

deep learning

clustering

cheminformatics

Top articles of Marek Śmieja

Title

Journal

Author(s)

Publication Date

StyleAutoEncoder for Manipulating Image Attributes Using Pre-trained StyleGAN

Andrzej Bedychaj

Jacek Tabor

Marek Śmieja

2024/4/25

Multi-Label Conditional Generation From Pre-Trained Models

IEEE Transactions on Pattern Analysis and Machine Intelligence

Magdalena Proszewska

Maciej Wołczyk

Maciej Zieba

Patryk Wielopolski

Łukasz Maziarka

...

2024/3/26

ADMET-PrInt: Evaluation of ADMET Properties: Prediction and Interpretation

Journal of Chemical Information and Modeling

Ewelina Jamrozik

Marek Śmieja

Sabina Podlewska

2024/2/19

Face Identity-Aware Disentanglement in StyleGAN

Adrian Suwała

Bartosz Wójcik

Magdalena Proszewska

Jacek Tabor

Przemysław Spurek

...

2024

Hypertab: Hypernetwork approach for deep learning on small tabular datasets

Witold Wydmański

Oleksii Bulenok

Marek Śmieja

2023/10/9

ChiENN: Embracing Molecular Chirality with Graph Neural Networks

Piotr Gaiński

Michał Koziarski

Jacek Tabor

Marek Śmieja

2023/9/17

r-softmax: Generalized Softmax with Controllable Sparsity Rate

Klaudia Bałazy

Łukasz Struski

Marek Śmieja

Jacek Tabor

2023/6/26

Augmentation-aware self-supervised learning with guided projector

arXiv preprint arXiv:2306.06082

Marcin Przewięźlikowski

Mateusz Pyla

Bartosz Zieliński

Bartłomiej Twardowski

Jacek Tabor

...

2023/5/31

Hebbian Continual Representation Learning

arXiv preprint arXiv:2207.04874

Paweł Morawiecki

Andrii Krutsylo

Maciej Wołczyk

Marek Śmieja

2022/6/28

Zero time waste in pre-trained early exit neural networks

Neural Networks

Bartosz Wójcik

Marcin Przewiȩźlikowski

Filip Szatkowski

Maciej Wołczyk

Klaudia Bałazy

...

2023/11/1

SONGs: Self-Organizing Neural Graphs

Łukasz Struski

Tomasz Danel

Marek Śmieja

Jacek Tabor

Bartosz Zieliński

2023

OneFlow: One-class flow for anomaly detection based on a minimal volume region

IEEE Transactions on Pattern Analysis and Machine Intelligence

Łukasz Maziarka

Marek Smieja

Marcin Sendera

Jacek Tabor

Przemysaw Spurek

2021/8/30

SLOVA: Uncertainty estimation using single label one-vs-all classifier

Applied Soft Computing

Bartosz Wójcik

Jacek Grela

Marek Śmieja

Krzysztof Misztal

Jacek Tabor

2022/9/1

Plugen: Multi-label conditional generation from pre-trained models

Proceedings of the AAAI Conference on Artificial Intelligence

Maciej Wołczyk

Magdalena Proszewska

Łukasz Maziarka

Maciej Zieba

Patryk Wielopolski

...

2022/6/28

Semi-supervised clustering via information-theoretic markov chain aggregation

Sophie Steger

Bernhard C Geiger

Marek Śmieja

2022/4/25

Głębokie uczenie: wprowadzenie

Jacek Tabor

Marek Śmieja

Łukasz Struski

Przemysław Spurek

Maciej Wołczyk

2022

MisConv: Convolutional Neural Networks for Missing Data

Marcin Przewięźlikowski

Marek Śmieja

Łukasz Struski

Jacek Tabor

2022

Zero time waste: Recycling predictions in early exit neural networks

Advances in Neural Information Processing Systems

Maciej Wołczyk

Bartosz Wójcik

Klaudia Bałazy

Igor T Podolak

Jacek Tabor

...

2021/12/6

Adversarial examples detection and analysis with layer-wise autoencoders

Bartosz Wójcik

Paweł Morawiecki

Marek Śmieja

Tomasz Krzyżek

Przemysław Spurek

...

2021/11/1

Pharmacoprint: a combination of a pharmacophore fingerprint and artificial intelligence as a tool for Computer-aided drug design

Journal of chemical information and modeling

Dawid Warszycki

Łukasz Struski

Marek Smieja

Rafał Kafel

Rafał Kurczab

2021/9/22

See List of Professors in Marek Śmieja University(Uniwersytet Jagiellonski)

Co-Authors

academic-engine