Igor T. Podolak

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 19

Top Topics

Generative Model

Hidden Variables

Discriminative Learning Framework

Active Learning

Top Venues

J. Cheminformatics

Publications

Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski
Relative molecule self-attention transformer. J. Cheminformatics 16 (1) (2024)
Bartosz Wójcik, Marcin Przewiezlikowski, Filip Szatkowski, Maciej Wolczyk, Klaudia Balazy, Bartlomiej Krzepkowski, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski
Zero time waste in pre-trained early exit neural networks. Neural Networks 168 (2023)
Tomasz Danel, Jan Leski, Sabina Podlewska, Igor T. Podolak
Docking-based generative approaches in the search for new drug candidates. CoRR (2023)
Szymon Knop, Marcin Mazur, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak
Generative models with kernel distance in data space. Neurocomputing 487 (2022)
Szymon Knop, Przemyslaw Spurek, Marcin Mazur, Jacek Tabor, Igor T. Podolak
Batch Size Reconstruction-Distribution Trade-Off In Kernel Based Generative Autoencoders. ICIP (2022)
Stefan Mordalski, Agnieszka Wojtuch, Igor T. Podolak, Rafal Kurczab, Andrzej J. Bojarski
2D SIFt: a matrix of ligand-receptor interactions. J. Cheminformatics 13 (1) (2021)
Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. CoRR (2021)
Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel Morkisz, Stanislaw Jastrzebski
Relative Molecule Self-Attention Transformer. CoRR (2021)
Maciej Wolczyk, Bartosz Wójcik, Klaudia Balazy, Igor T. Podolak, Jacek Tabor, Marek Smieja, Tomasz Trzcinski
Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. NeurIPS (2021)
Szymon Knop, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski
Cramer-Wold Auto-Encoder. J. Mach. Learn. Res. 21 (2020)
Szymon Knop, Marcin Mazur, Przemyslaw Spurek, Jacek Tabor, Igor T. Podolak
Generative models with kernel distance in data space. CoRR (2020)
Przemyslaw Spurek, Szymon Knop, Jacek Tabor, Igor T. Podolak, Bartosz Wójcik
One-element Batch Training by Moving Window. CoRR (2019)
Szymon Knop, Marcin Mazur, Jacek Tabor, Igor T. Podolak, Przemyslaw Spurek
Sliced generative models. CoRR (2019)
Lukasz Struski, Jacek Tabor, Igor T. Podolak, Aleksandra Nowak
Interpolation in generative models. CoRR (2019)
Damian Lesniak, Igor Sieradzki, Igor T. Podolak
Distribution-Interpolation Trade off in Generative Models. ICLR (Poster) (2019)
Igor T. Podolak, Adam Roman, Arkadiusz Czekajski, Damian Lesniak, Bartosz Zielinski
Variational auto-encoders for generating feature-preserving automata. NCMA (2019)
Igor T. Podolak, Adam Roman, Marek Szykula, Bartosz Zielinski
A machine learning approach to synchronization of automata. Expert Syst. Appl. 97 (2018)
Jacek Tabor, Szymon Knop, Przemyslaw Spurek, Igor T. Podolak, Marcin Mazur, Stanislaw Jastrzebski
Cramer-Wold AutoEncoder. CoRR (2018)
Damian Lesniak, Igor Sieradzki, Igor T. Podolak
On Latent Distributions Without Finite Mean in Generative Models. CoRR (2018)
Wojciech M. Czarnecki, Igor T. Podolak
Adaptive Active Learning as a Multi-armed Bandit Problem. ECAI (2014)
Igor T. Podolak, Stanislaw K. Jastrzebski
Density Invariant Detection of Osteoporosis Using Growing Neural Gas. CORES (2013)
Igor T. Podolak, Adam Roman
Theoretical Foundations and Experimental Results for a Hierarchical Classifier with Overlapping Clusters. Comput. Intell. 29 (2) (2013)
Wojciech M. Czarnecki, Igor T. Podolak
Machine Learning with Known Input Data Uncertainty Measure. CISIM (2013)
Igor T. Podolak, Adam Roman, Dariusz Jedrzejczyk
Application of Hierarchical Classifier to Minimal Synchronizing Word Problem. ICAISC (1) (2012)
Kamil Bartocha, Igor T. Podolak
Classifier Ensembles for Virtual Concept Drift - The DEnBoost Algorithm. HAIS (2) (2011)
Igor T. Podolak, Adam Roman
CORES: fusion of supervised and unsupervised training methods for a multi-class classification problem. Pattern Anal. Appl. 14 (4) (2011)
Igor T. Podolak, Adam Roman
Risk Estimation for Hierarchical Classifier. HAIS (1) (2011)
Stanislaw Brodowski, Igor T. Podolak
Hierarchical Estimator. Expert Syst. Appl. 38 (10) (2011)
Igor T. Podolak, Adam Roman
Risk function estimation for subproblems in a hierarchical classifier. Pattern Recognit. Lett. 32 (15) (2011)
Igor T. Podolak, Kamil Bartocha
A Hierarchical Classifier with Growing Neural Gas Clustering. ICANNGA (2009)
Piotr Kalita, Igor T. Podolak, Adam Roman, Bartosz Bierkowski
Algorithm for Intelligent Prediction of Requests in Business Systems. SOFSEM (2008)
Igor T. Podolak
Hierarchical classifier with overlapping class groups. Expert Syst. Appl. 34 (1) (2008)
Igor T. Podolak
Hierarchical Rules for a Hierarchical Classifier. ICANNGA (1) (2007)
Igor T. Podolak, Slawomir Biel, Marcin Bobrowski
Hierarchical Classifier. PPAM (2005)
Dihua Xi, Igor T. Podolak, Seong-Whan Lee
Facial Component Extraction and Face Recognition with Support Vector Machines. FGR (2002)
Igor T. Podolak, Seong-Whan Lee, Andrzej Bielecki, Elzbieta Majkut
A Hybrid Neural System for Phonematic Transformation. ICPR (2000)
Igor T. Podolak
Functional graph model of a neural network. IEEE Trans. Syst. Man Cybern. Part B 28 (6) (1998)