Igor T. Podolak

About Igor T. Podolak

Igor T. Podolak, With an exceptional h-index of 13 and a recent h-index of 10 (since 2020), a distinguished researcher at Uniwersytet Jagiellonski, specializes in the field of Machine Learning, Artificial Intelligence, Complex Hierarchical Classification Systems, Bioinformatics.

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

Relative molecule self-attention transformer

Zero time waste in pre-trained early exit neural networks

Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models

Docking-based generative approaches in the search for new drug candidates

Batch Size Reconstruction–Distribution Trade–Off In Kernel Based Generative Autoencoders

Decoding working memory-related information from repeated psychophysiological EEG experiments using convolutional and contrastive neural networks

Generative models with kernel distance in data space

Neural spatio-temporal patterns of information processing related to cognitive conflict and correct or false recognitions

Igor T. Podolak Information

University

Position

Faculty of Mathamatics and Computer Science Poland

Citations(all)

502

Citations(since 2020)

262

Cited By

399

hIndex(all)

13

hIndex(since 2020)

10

i10Index(all)

17

i10Index(since 2020)

10

Email

University Profile Page

Google Scholar

Igor T. Podolak Skills & Research Interests

Machine Learning

Artificial Intelligence

Complex Hierarchical Classification Systems

Bioinformatics

Top articles of Igor T. Podolak

Title

Journal

Author(s)

Publication Date

Relative molecule self-attention transformer

Journal of Cheminformatics

Łukasz Maziarka

Dawid Majchrowski

Tomasz Danel

Piotr Gaiński

Jacek Tabor

...

2024/1/3

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

Feature-Based Interpolation and Geodesics in the Latent Spaces of Generative Models

IEEE Transactions on Neural Networks and Learning Systems

Łukasz Struski

Michał Sadowski

Tomasz Danel

Jacek Tabor

Igor T Podolak

2023/3/10

Docking-based generative approaches in the search for new drug candidates

Tomasz Danel

Jan Łęski

Sabina Podlewska

Igor T Podolak

2023/2/1

Batch Size Reconstruction–Distribution Trade–Off In Kernel Based Generative Autoencoders

Szymon Knop

Przemysław Spurek

Marcin Mazur

Jacek Tabor

Igor Podolak

2022/10/16

Decoding working memory-related information from repeated psychophysiological EEG experiments using convolutional and contrastive neural networks

Journal of Neural Engineering

Jarosław Żygierewicz

Romuald A Janik

Igor T Podolak

Alan Drozd

Urszula Malinowska

...

2022/9/5

Generative models with kernel distance in data space

Neurocomputing

Szymon Knop

Marcin Mazur

Przemysław Spurek

Jacek Tabor

Igor Podolak

2022/5/28

Neural spatio-temporal patterns of information processing related to cognitive conflict and correct or false recognitions

Scientific Reports

Romuald A Janik

Igor T Podolak

Łukasz Struski

Anna Ceglarek

Koryna Lewandowska

...

2022/3/28

2D SIFt: a matrix of ligand-receptor interactions

Journal of Cheminformatics

Stefan Mordalski

Agnieszka Wojtuch

Igor Podolak

Rafał Kurczab

Andrzej J Bojarski

2021/12

RELATIVE MOLECULE SELF-ATTENTION TRANS

arXiv preprint arXiv:2110.05841

Łukasz Maziarka

Dawid Majchrowski

Tomasz Danel

Piotr Gainski

Jacek Tabor

...

2021/10

Deep convolutional neural network for preliminary in-field classification of lichen species

biosystems engineering

Agnieszka Galanty

Tomasz Danel

Michał Węgrzyn

Irma Podolak

Igor Podolak

2021/4/1

Machine Learning-Based Identification of Suicidal Risk in Patients With Schizophrenia Using Multi-Level Resting-State fMRI Features

Frontiers in neuroscience

Bartosz Bohaterewicz

Anna M Sobczak

Igor Podolak

Bartosz Wójcik

Dagmara Mȩtel

...

2021/1/11

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

Cramer-Wold auto-encoder

Journal of Machine Learning Research

Szymon Knop

Jacek Tabor

Igor Podolak

Marcin Mazur

2020

De Novo Drug Design with a Docking Score Proxy

Machine Learning for Molecules Workshop at NeurIPS

Tomasz Danel

Maciej Szymczak

Łukasz Maziarka

Igor Podolak

Jacek Tabor

...

2020

See List of Professors in Igor T. Podolak University(Uniwersytet Jagiellonski)

Co-Authors

academic-engine