Loop profiling tool for HPC code inspection as an efficient method of FPGA based acceleration. - Marcin Pietron; Pawel Russek; Kazimierz Wiatr (Int. J. Appl. Math. Comput. Sci., 2010)

Comparison of GPU and FPGA Implementation of SVM Algorithm for Fast Image Segmentation. - Marcin Pietron; Maciej Wielgosz; Dominik Zurek; Ernest Jamro; Kazimierz Wiatr (ARCS, 2013)

Accelerating Select where and Select Join Queries on a GPU. - Marcin Pietron; Pawel Russek; Kazimierz Wiatr (Comput. Sci., 2013)

Comparison of Hybrid Sorting Algorithms Implemented on Different Parallel Hardware Platforms. - Dominik Zurek; Marcin Pietron; Maciej Wielgosz; Kazimierz Wiatr (Comput. Sci., 2013)

Implementation of a System for Fast Text Search and Document Comparison. - Maciej Wielgosz; Marcin Janiszewski; Pawel Russek; Marcin Pietron; Ernest Jamro; Kazimierz Wiatr (Intelligent Tools for Building a Scientific Information Platform, 2014)

GPGPU for Difficult Black-box Problems. - Marcin Pietron; Aleksander Byrski; Marek Kisiel-Dorohinicki (ICCS, 2015)

Using Spatial Pooler of Hierarchical Temporal Memory for object classification in noisy video streams. - Maciej Wielgosz; Marcin Pietron; Kazimierz Wiatr (FedCSIS, 2016)

Study of the Parallel Techniques for Dimensionality Reduction and Its Impact on Performance of the Text Processing Algorithms. - Marcin Pietron; Maciej Wielgosz; Pawel Russek; Kazimierz Wiatr (ICAART (1), 2016)

Parallel Implementation of Spatial Pooler in Hierarchical Temporal Memory. - Marcin Pietron; Maciej Wielgosz; Kazimierz Wiatr (ICAART (2), 2016)

Comparison of SVM and Ontology-Based Text Classification Methods. - Krzysztof Wróbel 002; Maciej Wielgosz; Aleksander Smywinski-Pohl; Marcin Pietron (ICAISC (1), 2016)

Formal Analysis of HTM Spatial Pooler Performance Under Predefined Operation Conditions. - Marcin Pietron; Maciej Wielgosz; Kazimierz Wiatr (IJCRS, 2016)

OpenCL-accelerated object classification in video streams using Spatial Pooler of Hierarchical Temporal Memory. - Maciej Wielgosz; Marcin Pietron (CoRR, 2016)

Noisy video classification with Spatial Pooler of Hierarchical Temporal Memory. - Maciej Wielgosz; Marcin Pietron (CoRR, 2016)

Toward hybrid platform for evolutionary computations of hard discrete problems. - Dominik Zurek; Kamil Pietak; Marcin Pietron; Marek Kisiel-Dorohinicki (ICCS, 2017)

Experiment on Methods for Clustering and Categorization of Polish Text. - Maciej Wielgosz; Rafal Fraczek; Pawel Russek; Marcin Pietron; Agnieszka Dabrowska-Boruch; Ernest Jamro; Kazimierz Wiatr (Comput. Informatics, 2017)

Evaluation and Implementation of n-Gram-Based Algorithm for Fast Text Comparison. - Maciej Wielgosz; Pawel Szczepka; Pawel Russek; Ernest Jamro; Kazimierz Wiatr; Marcin Pietron; Dominik Zurek (Comput. Informatics, 2017)

Improving text classification with vectors of reduced precision. - Krzysztof Wróbel 002; Maciej Wielgosz; Marcin Pietron; Michal Karwatowski; Aleksander Smywinski-Pohl (CoRR, 2017)

Using Spatial Pooler of Hierarchical Temporal Memory to classify noisy videos with predefined complexity. - Maciej Wielgosz; Marcin Pietron (Neurocomputing, 2017)

Implementation of Digital Watermarking Algorithms in Parallel Hardware Accelerators. - Andrzej Glowacz; Marcin Pietron (Int. J. Parallel Program., 2017)

Leveraging heterogeneous parallel platform in solving hard discrete optimization problems with metaheuristics. - Marcin Pietron; Aleksander Byrski; Marek Kisiel-Dorohinicki (J. Comput. Sci., 2017)

Towards a Stable Quantized Convolutional Neural Networks: An Embedded Perspective. - Mo'taz Al-Hami; Marcin Pietron; Raúl A. Casas; Samer L. Hijazi; Piyush Kaul (ICAART (2), 2018)

Improving Text Classification with Vectors of Reduced Precision. - Krzysztof Wróbel 002; Maciej Wielgosz; Marcin Pietron; Michal Karwatowski; Jerzy Duda; Aleksander Smywinski-Pohl (ICAART (2), 2018)

FPGA Implementation of Procedures for Video Quality Assessment. - Maciej Wielgosz; Michal Karwatowski; Marcin Pietron; Kazimierz Wiatr (Comput. Sci., 2018)

Convolutional neural network compression for natural language processing. - Krzysztof Wróbel 002; Marcin Pietron; Maciej Wielgosz; Michal Karwatowski; Kazimierz Wiatr (CoRR, 2018)

Method for Hybrid Precision Convolutional Neural Network Representation. - Mo'taz Al-Hami; Marcin Pietron; Rishi Kumar; Raúl A. Casas; Samer L. Hijazi; Chris Rowen (CoRR, 2018)

Ensemble Approach for Natural Language Question Answering Problem. - Anna Aniol; Marcin Pietron; Jerzy Duda (CANDAR Workshops, 2019)

Fast Compression and Optimization of Deep Learning Models for Natural Language Processing. - Marcin Pietron; Michal Karwatowski; Maciej Wielgosz; Jerzy Duda (CANDAR Workshops, 2019)

Improvements of Monotonicity Approach to Solve Interval Parametric Linear Systems. - Iwona Skalna; Marcin Pietron; Milan Hladík (PPAM (2), 2019)

Ensemble approach for natural language question answering problem. - Anna Aniol; Marcin Pietron (CoRR, 2019)

Striving for performance of discrete optimisation via memetic agent-based systems in a hybrid CPU/GPU environment. - Kamil Pietak; Dominik Zurek; Marcin Pietron; Andrzej Dymara; Marek Kisiel-Dorohinicki (J. Comput. Sci., 2019)

Retrain or Not Retrain? - Efficient Pruning Methods of Deep CNN Networks. - Marcin Pietron; Maciej Wielgosz (ICCS (3), 2020)

Compression of Convolutional Neural Network for Natural Language Processing. - Krzysztof Wróbel 002; Michal Karwatowski; Maciej Wielgosz; Marcin Pietron; Kazimierz Wiatr (Comput. Sci., 2020)

Training with reduced precision of a support vector machine model for text classification. - Dominik Zurek; Marcin Pietron (CoRR, 2020)

When deep learning models on GPU can be accelerated by taking advantage of unstructured sparsity. - Marcin Pietron; Dominik Zurek (CoRR, 2020)

Methodologies of Compressing a Stable Performance Convolutional Neural Networks in Image Classification. - Mo'taz Al-Hami; Marcin Pietron; Raúl A. Casas; Maciej Wielgosz (Neural Process. Lett., 2020)

New Variants of SDLS Algorithm for LABS Problem Dedicated to GPGPU Architectures. - Dominik Zurek; Kamil Pietak; Marcin Pietron; Marek Kisiel-Dorohinicki (ICCS (1), 2021)

Accelerating Deep Convolutional Neural on GPGPU. - Dominik Zurek; Marcin Pietron; Kazimierz Wiatr (SAI (2), 2021)

Ensemble neuroevolution based approach for multivariate time series anomaly detection. - Kamil Faber; Dominik Zurek; Marcin Pietron; Kamil Pietak (CoRR, 2021)

Fast and scalable neuroevolution deep learning architecture search for multivariate anomaly detection. - Marcin Pietron; Dominik Zurek; Kamil Faber (CoRR, 2021)

Neuroevolution deep learning architecture search for estimation of river surface elevation from photogrammetric Digital Surface Models. - Radoslaw Szostak; Marcin Pietron; Miroslaw Zimnoch; Przemyslaw Wachniew; Pawel Cwiakala; Edyta Puniach (CoRR, 2021)

Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction. - Marcin Pietron; Dominik Zurek (CoRR, 2021)

Ensemble Neuroevolution-Based Approach for Multivariate Time Series Anomaly Detection. - Kamil Faber; Marcin Pietron; Dominik Zurek (Entropy, 2021)

Canine age classification using Deep Learning as a step towards preventive medicine in animals. - Szymon Mazurek; Maciej Wielgosz; Jakub Caputa; Rafal Fraczek; Michal Karwatowski; Jakub Grzeszczyk; Daria Lukasik; Anna Smiech; Pawel Russek; Ernest Jamro; Agnieszka Dabrowska-Boruch; Marcin Pietron; et al. (FedCSIS, 2022)

A Deep Neural Network as a TABU Support in Solving LABS Problem. - Dominik Zurek; Marcin Pietron; Kamil Pietak; Marek Kisiel-Dorohinicki (ICCS (1), 2022)

Context based lemmatizer for Polish language. - Michal Karwatowski; Marcin Pietron (CoRR, 2022)

Chosen methods of improving object recognition of small objects with weak recognizable features. - Magdalena Stachon; Marcin Pietron (CoRR, 2022)

Ada-QPacknet - Multi-Task Forget-Free Continual Learning with Quantization Driven Adaptive Pruning. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (ECAI, 2023)

Chosen Methods of Improving Small Object Recognition with Weak Recognizable Features. - Magdalena Stachon; Marcin Pietron (FICC (2), 2023)

Transformed-*: A domain-incremental lifelong learning scenario generation framework. - Dominik Zurek; Roberto Corizzo; Michal Karwatowski; Marcin Pietron; Kamil Faber (IJCNN, 2023)

J-Parallelio - automatic parallelization framework for Java virtual machine code. - Krzysztof Stuglik; Piotr Listkiewicz; Mateusz Kulczyk; Marcin Pietron (CoRR, 2023)

Segmentation of the veterinary cytological images for fast neoplastic tumors diagnosis. - Jakub Grzeszczyk; Michal Karwatowski; Daria Lukasik; Maciej Wielgosz; Pawel Russek; Szymon Mazurek; Jakub Caputa; Rafal Fraczek; Anna Smiech; Ernest Jamro; Sebastian Koryciak; Agnieszka Dabrowska-Boruch; et al. (CoRR, 2023)

AD-NEV: A Scalable Multi-level Neuroevolution Framework for Multivariate Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2023)

Estimation of River Water Surface Elevation Using UAV Photogrammetry and Machine Learning. - Radoslaw Szostak; Marcin Pietron; Przemyslaw Wachniew; Miroslaw Zimnoch; Pawel Cwiakala (CoRR, 2023)

Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology. - Jakub Caputa; Maciej Wielgosz; Daria Lukasik; Pawel Russek; Jakub Grzeszczyk; Michal Karwatowski; Szymon Mazurek; Rafal Fraczek; Anna Smiech; Ernest Jamro; Sebastian Koryciak; Agnieszka Dabrowska-Boruch; et al. (CoRR, 2023)

Using simulation to calibrate real data acquisition in veterinary medicine. - Krystian Strzalka; Szymon Mazurek; Maciej Wielgosz; Pawel Russek; Jakub Caputa; Daria Lukasik; Jan Krupinski; Jakub Grzeszczyk; Michal Karwatowski; Rafal Fraczek; Ernest Jamro; Marcin Pietron; et al. (CoRR, 2023)

Computer-Aided Cytology Diagnosis in Animals: CNN-Based Image Quality Assessment for Accurate Disease Classification. - Jan Krupinski; Maciej Wielgosz; Szymon Mazurek; Krystian Strzalka; Pawel Russek; Jakub Caputa; Daria Lukasik; Jakub Grzeszczyk; Michal Karwatowski; Rafal Fraczek; Ernest Jamro; Marcin Pietron; et al. (CoRR, 2023)

Ada-QPacknet - adaptive pruning with bit width reduction as an efficient continual learning method without forgetting. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2023)

Speedup deep learning models on GPU by taking advantage of efficient unstructured pruning and bit-width reduction. - Marcin Pietron; Dominik Zurek; Bartlomiej Sniezynski (J. Comput. Sci., 2023)

RLEM: Deep Reinforcement Learning Ensemble Method for Aircraft Recovery Problem. - Dominik Zurek; Marcin Pietron; Szymon Piórkowski; Michal Karwatowski; Kamil Faber (IEEE Big Data, 2024)

A Deep Double Q-Learning as a SDLS support in solving LABS problem. - Dominik Zurek; Marcin Pietron; Kamil Pietak; Kamil Faber (ESANN, 2024)

AD-NEv++ - The multi-architecture neuroevolution-based multivariate anomaly detection framework. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo; Anna Wójcik (GECCO Companion, 2024)

Towards Efficient Deep Autoencoders for Multivariate Time Series Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (ICCS (3), 2024)

Efficient Argument Classification with Compact Language Models and ChatGPT-4 Refinements. - Marcin Pietron; Rafal Olszowski; Jakub Gomulka (ICCCI (1), 2024)

AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (CoRR, 2024)

Solving Multi-Goal Robotic Tasks with Decision Transformer. - Paul Gajewski; Dominik Zurek; Marcin Pietron; Kamil Faber (CoRR, 2024)

Estimation of Small-Stream Water Surface Elevation Using UAV Photogrammetry and Deep Learning. - Radoslaw Szostak; Marcin Pietron; Przemyslaw Wachniew; Miroslaw Zimnoch; Pawel Cwiakala (Remote. Sens., 2024)

From MNIST to ImageNet and back: benchmarking continual curriculum learning. - Kamil Faber; Dominik Zurek; Marcin Pietron; Nathalie Japkowicz; Antonio Vergari; Roberto Corizzo (Mach. Learn., 2024)

TinySubNets: An Efficient and Low Capacity Continual Learning Strategy. - Marcin Pietron; Kamil Faber; Dominik Zurek; Roberto Corizzo (AAAI, 2025)

AD-NEv: A Scalable Multilevel Neuroevolution Framework for Multivariate Anomaly Detection. - Marcin Pietron; Dominik Zurek; Kamil Faber; Roberto Corizzo (IEEE Trans. Neural Networks Learn. Syst., 2025)

xLSTMAD: A Powerful xLSTM-based Method for Anomaly Detection. - Kamil Faber; Marcin Pietron; Dominik Zurek; Roberto Corizzo (CoRR, 2025)

A comprehensive study of LLM-based argument classification: from LLAMA through GPT-4o to Deepseek-R1. - Marcin Pietron; Rafal Olszowski; Jakub Gomulka; Filip Gampel; Andrzej Tomski (CoRR, 2025)