Forming Classifier Ensembles with Deterministic Feature Subspaces. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (FedCSIS, 2016)

Examination of the Deep Neural Networks in Classification of Distorted Signals. - Michal Koziarski; Boguslaw Cyganek (ICAISC (2), 2016)

Deep Neural Image Denoising. - Michal Koziarski; Boguslaw Cyganek (ICCVG, 2016)

Radial-Based Approach to Imbalanced Data Oversampling. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (HAIS, 2017)

CCR: A combined cleaning and resampling algorithm for imbalanced data classification. - Michal Koziarski; Michal Wozniak 001 (Int. J. Appl. Math. Comput. Sci., 2017)

Analysis of group evolution prediction in complex networks. - Stanislaw Saganowski; Piotr Bródka; Michal Koziarski; Przemyslaw Kazienko (CoRR, 2017)

Image recognition with deep neural networks in presence of noise - Dealing with and taking advantage of distortions. - Michal Koziarski; Boguslaw Cyganek (Integr. Comput. Aided Eng., 2017)

The deterministic subspace method for constructing classifier ensembles. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (Pattern Anal. Appl., 2017)

Marine Snow Removal Using a Fully Convolutional 3D Neural Network Combined with an Adaptive Median Filter. - Michal Koziarski; Boguslaw Cyganek (CVAUI/IWCF/MIPPSNA@ICPR, 2018)

Convolutional Neural Network-Based Classification of Histopathological Images Affected by Data Imbalance. - Michal Koziarski; Bogdan Kwolek; Boguslaw Cyganek (FFER/DLPR@ICPR, 2018)

Impact of Low Resolution on Image Recognition with Deep Neural Networks: An Experimental Study. - Michal Koziarski; Boguslaw Cyganek (Int. J. Appl. Math. Comput. Sci., 2018)

A Multiresolution Grid Structure Applied to Seafloor Shape Modeling. - Wojciech Maleika; Michal Koziarski; Pawel Forczmanski (ISPRS Int. J. Geo Inf., 2018)

Radial-Based Undersampling Algorithm for Classification of Breast Cancer Histopathological Images Affected by Data Imbalance. - Michal Koziarski (CISP-BMEI, 2019)

Breast Cancer Classification on Histopathological Images Affected by Data Imbalance Using Active Learning and Deep Convolutional Neural Network. - Bogdan Kwolek; Michal Koziarski; Andrzej Bukala; Zbigniew Antosz; Boguslaw Olborski; Pawel Wasowicz; Jakub Swadzba; Boguslaw Cyganek (ICANN (Workshop), 2019)

The Impact of Distortions on the Image Recognition with Histograms of Oriented Gradients. - Andrzej Bukala; Michal Koziarski; Boguslaw Cyganek; Osman Nuri Koç; Alperen Kara (IP&C, 2019)

Radial-Based oversampling for noisy imbalanced data classification. - Michal Koziarski; Bartosz Krawczyk; Michal Wozniak 001 (Neurocomputing, 2019)

Classification of Histopathological Images using Scale-Invariant Feature Transform. - Andrzej Bukala; Boguslaw Cyganek; Michal Koziarski; Bogdan Kwolek; Boguslaw Olborski; Zbigniew Antosz; Jakub Swadzba; Piotr Sitkowski (VISIGRAPP (5: VISAPP), 2020)

The Choice of Feature Representation in Small-Scale MobileNet-Based Imbalanced Image Recognition. - Michal Koziarski; Boguslaw Cyganek; Kazimierz Wiatr (VISIGRAPP (4: VISAPP), 2020)

A Study on Pattern Recognition with the Histograms of Oriented Gradients in Distorted and Noisy Images. - Andrzej Bukala; Michal Koziarski; Boguslaw Cyganek; Osman Nuri Koç; Alperen Kara (J. Univers. Comput. Sci., 2020)

Combined Cleaning and Resampling algorithm for multi-class imbalanced data with label noise. - Michal Koziarski; Michal Wozniak 001; Bartosz Krawczyk (Knowl. Based Syst., 2020)

Radial-Based Undersampling for imbalanced data classification. - Michal Koziarski (Pattern Recognit., 2020)

Radial-Based Oversampling for Multiclass Imbalanced Data Classification. - Bartosz Krawczyk; Michal Koziarski; Michal Wozniak 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

CSMOUTE: Combined Synthetic Oversampling and Undersampling Technique for Imbalanced Data Classification. - Michal Koziarski (IJCNN, 2021)

Two-Stage Resampling for Convolutional Neural Network Training in the Imbalanced Colorectal Cancer Image Classification. - Michal Koziarski (IJCNN, 2021)

DiagSet: a dataset for prostate cancer histopathological image classification. - Michal Koziarski; Boguslaw Cyganek; Boguslaw Olborski; Zbigniew Antosz; Marcin Zydak; Bogdan Kwolek; Pawel Wasowicz; Andrzej Bukala; Jakub Swadzba; Piotr Sitkowski (CoRR, 2021)

Imbalanced data preprocessing techniques utilizing local data characteristics. - Michal Koziarski (CoRR, 2021)

RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification. - Michal Koziarski; Colin Bellinger; Michal Wozniak 001 (Mach. Learn., 2021)

Potential Anchoring for imbalanced data classification. - Michal Koziarski (Pattern Recognit., 2021)

Multicriteria Classifier Ensemble Learning for Imbalanced Data. - Weronika Wegier; Michal Koziarski; Michal Wozniak 001 (IEEE Access, 2022)

Optimized hybrid imbalanced data sampling for decision tree training. - Weronika Wegier; Michal Koziarski; Michal Wozniak 001 (GECCO Companion, 2023)

ChiENN: Embracing Molecular Chirality with Graph Neural Networks. - Piotr Gainski; Michal Koziarski; Jacek Tabor; Marek Smieja (ECML/PKDD (3), 2023)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (CoRR, 2023)

Crystal-GFN: sampling crystals with desirable properties and constraints. - Alex Hernández-García; Alexandre Duval; Alexandra Volokhova; Yoshua Bengio; Divya Sharma; Pierre Luc Carrier; Michal Koziarski; Victor Schmidt (CoRR, 2023)

Towards equilibrium molecular conformation generation with GFlowNets. - Alexandra Volokhova; Michal Koziarski; Alex Hernández-García; Cheng-Hao Liu; Santiago Miret; Pablo Lemos; Luca A. Thiede; Zichao Yan; Alán Aspuru-Guzik; Yoshua Bengio (CoRR, 2023)

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets. - Dominique Beaini; Shenyang Huang; Joao Alex Cunha; Zhiyi Li; Gabriela Moisescu-Pareja; Oleksandr Dymov; Samuel Maddrell-Mander; Callum McLean; Frederik Wenkel; Luis Müller; Jama Hussein Mohamud; Ali Parviz; et al. (ICLR, 2024)

RGFN: Synthesizable Molecular Generation Using GFlowNets. - Michal Koziarski; Andrei Rekesh; Dmytro Shevchuk; Almer van der Sloot; Piotr Gainski; Yoshua Bengio; Cheng-Hao Liu; Mike Tyers; Robert A. Batey (NeurIPS, 2024)

Towards DNA-Encoded Library Generation with GFlowNets. - Michal Koziarski; Mohammed Abukalam; Vedant Shah; Louis Vaillancourt; Doris Alexandra Schuetz; Moksh Jain; Almer van der Sloot; Mathieu Bourgey; Anne Marinier; Yoshua Bengio (CoRR, 2024)

RetroGFN: Diverse and Feasible Retrosynthesis using GFlowNets. - Piotr Gainski; Michal Koziarski; Krzysztof Maziarz; Marwin H. S. Segler; Jacek Tabor; Marek Smieja (CoRR, 2024)

Cell Morphology-Guided Small Molecule Generation with GFlowNets. - Stephen Zhewen Lu; Ziqing Lu; Ehsan Hajiramezanali; Tommaso Biancalani; Yoshua Bengio; Gabriele Scalia; Michal Koziarski (CoRR, 2024)

Local neighborhood encodings for imbalanced data classification. - Michal Koziarski; Michal Wozniak 001 (Mach. Learn., 2024)

Action abstractions for amortized sampling. - Oussama Boussif; Léna Néhale Ezzine; Joseph D. Viviano; Michal Koziarski; Moksh Jain; Nikolay Malkin; Emmanuel Bengio; Rim Assouel; Yoshua Bengio (ICLR, 2025)

Diverse and feasible retrosynthesis using GFlowNets. - Piotr Gainski; Michal Koziarski; Krzysztof Maziarz; Marwin H. S. Segler; Jacek Tabor; Marek Smieja (Inf. Sci., 2025)

Learning Decision Trees as Amortized Structure Inference. - Mohammed Mahfoud; Ghait Boukachab; Michal Koziarski; Alex Hernández-García; Stefan Bauer; Yoshua Bengio; Nikolay Malkin (CoRR, 2025)

Scalable and Cost-Efficient de Novo Template-Based Molecular Generation. - Piotr Gainski; Oussama Boussif; Andrei Rekesh; Dmytro Shevchuk; Ali Parviz; Mike Tyers; Robert A. Batey; Michal Koziarski (CoRR, 2025)

Measuring Scientific Capabilities of Language Models with a Systems Biology Dry Lab. - Haonan Duan 002; Stephen Zhewen Lu; Caitlin Fiona Harrigan; Nishkrit Desai; Jiarui Lu; Michal Koziarski; Leonardo Cotta; Chris J. Maddison (CoRR, 2025)

SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling. - Andrei Rekesh; Miruna T. Cretu; Dmytro Shevchuk; Vignesh Ram Somnath; Pietro Liò; Robert A. Batey; Mike Tyers; Michal Koziarski; Cheng-Hao Liu (CoRR, 2025)