Intensive versus Non-intensive Actor-Critic Reinforcement Learning Algorithms. - Pawel Wawrzynski; Andrzej Pacut (ICAISC, 2004)

Model-free off-policy reinforcement learning in continuous environment. - Pawel Wawrzynski; Andrzej Pacut (IJCNN, 2004)

Reinforcement Learning in Quasi-Continuous Time. - Pawel Wawrzynski; Andrzej Pacut (CIMCA/IAWTIC, 2005)

Reinforcement Learning in Fine Time Discretization. - Pawel Wawrzynski (ICANNGA (1), 2007)

Predictive Control for Artificial Intelligence in Computer Games. - Pawel Wawrzynski; Jaroslaw Arabas; Pawel Cichosz (ICAISC, 2008)

A Cat-Like Robot Real-Time Learning to Run. - Pawel Wawrzynski (ICANNGA, 2009)

Real-time reinforcement learning by sequential Actor-Critics and experience replay. - Pawel Wawrzynski (Neural Networks, 2009)

Fixed point method of step-size estimation for on-line neural network training. - Pawel Wawrzynski (IJCNN, 2010)

Fixed point method for autonomous on-line neural network training. - Pawel Wawrzynski; Bartosz Papis (Neurocomputing, 2011)

Autonomous Reinforcement Learning with Experience Replay for Humanoid Gait Optimization. - Pawel Wawrzynski (INNS-WC, 2012)

dotRL: A platform for rapid Reinforcement Learning methods development and validation. - Bartosz Papis; Pawel Wawrzynski (FedCSIS, 2013)

Learning population of spiking neural networks with perturbation of conductances. - Piotr Suszynski; Pawel Wawrzynski (IJCNN, 2013)

Robust velocity estimation for legged robot using on-board sensors data fusion. - Pawel Wawrzynski; Jakub Mozaryn; Jan Klimaszewski (MMAR, 2013)

Design process and experimental verification of the quadruped robot wave gait. - Jakub Mozaryn; Jan Klimaszewski; Pawel Kolodziejczyk; Dariusz Swieczkowski-Feiz; Pawel Wawrzynski (MMAR, 2014)

Reinforcement Learning with Experience Replay for Model-Free Humanoid Walking Optimization. - Pawel Wawrzynski (Int. J. Humanoid Robotics, 2014)

Comparison of two efficient control strategies for two-wheeled balancing robot. - Michal Majczak; Pawel Wawrzynski (MMAR, 2015)

Robot's velocity and tilt estimation through computationally efficient fusion of proprioceptive sensors readouts. - Pawel Wawrzynski (MMAR, 2015)

Robust estimation of walking robots velocity and tilt using proprioceptive sensors data fusion. - Pawel Wawrzynski; Jakub Mozaryn; Jan Klimaszewski (Robotics Auton. Syst., 2015)

Parameter-Free On-line Deep Learning. - Pawel Wawrzynski (AUTOMATION, 2017)

ASD+M: Automatic parameter tuning in stochastic optimization and on-line learning. - Pawel Wawrzynski (Neural Networks, 2017)

Efficient on-line learning with diagonal approximation of loss function Hessian. - Pawel Wawrzynski (IJCNN, 2019)

Numerosity Representation in InfoGAN: An Empirical Study. - Andrea Zanetti; Alberto Testolin; Marco Zorzi; Pawel Wawrzynski (IWANN (2), 2019)

Machine Learning-Based Predictions of Customers' Decisions in Car Insurance. - Lukasz Neumann; Robert M. Nowak; Rafal Okuniewski; Pawel Wawrzynski (Appl. Artif. Intell., 2019)

A Framework for Reinforcement Learning with Autocorrelated Actions. - Marcin Szulc; Jakub Lyskawa; Pawel Wawrzynski (ICONIP (2), 2020)

DCT-Conv: Coding filters in convolutional networks with Discrete Cosine Transform. - Karol Cheinski; Pawel Wawrzynski (IJCNN, 2020)

Automatic hyperparameter tuning in on-line learning: Classic Momentum and ADAM. - Pawel Wawrzynski; Pawel Zawistowski; Lukasz Lepak (IJCNN, 2020)

BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. - Kamil Deja; Pawel Wawrzynski; Daniel Marczak; Wojciech Masarczyk; Tomasz Trzcinski (IJCNN, 2021)

Deep Memory Update. - Lukasz Neumann; Pawel Wawrzynski (CoRR, 2021)

Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning. - Kamil Deja; Pawel Wawrzynski; Daniel Marczak; Wojciech Masarczyk; Tomasz Trzcinski (CoRR, 2021)

Reinforcement Learning for on-line Sequence Transformation. - Grzegorz Rypesc; Lukasz Lepak; Pawel Wawrzynski (FedCSIS, 2022)

ReGAE: Graph Autoencoder Based on Recursive Neural Networks. - Adam Malkowski; Jakub Grzechocinski; Pawel Wawrzynski (ICONIP (4), 2022)

Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning. - Kamil Deja; Pawel Wawrzynski; Wojciech Masarczyk; Daniel Marczak; Tomasz Trzcinski (IJCAI, 2022)

Logarithmic Continual Learning. - Wojciech Masarczyk; Pawel Wawrzynski; Daniel Marczak; Kamil Deja; Tomasz Trzcinski (IEEE Access, 2022)

Graph autoencoder with constant dimensional latent space. - Adam Malkowski; Jakub Grzechocinski; Pawel Wawrzynski (CoRR, 2022)

Reinforcement learning with experience replay and adaptation of action dispersion. - Pawel Wawrzynski; Wojciech Masarczyk; Mateusz Ostaszewski (CoRR, 2022)

Emergency action termination for immediate reaction in hierarchical reinforcement learning. - Michal Bortkiewicz; Jakub Lyskawa; Pawel Wawrzynski; Mateusz Ostaszewski; Artur Grudkowski; Tomasz Trzcinski (CoRR, 2022)

Actor-Critic with Variable Time Discretization via Sustained Actions. - Jakub Lyskawa; Pawel Wawrzynski (ICONIP (1), 2023)

Least Redundant Gated Recurrent Neural Network. - Lukasz Neumann; Lukasz Lepak; Pawel Wawrzynski (IJCNN, 2023)

Reinforcement learning for optimization of energy trading strategy. - Lukasz Lepak; Pawel Wawrzynski (CoRR, 2023)

Subgoal Reachability in Goal Conditioned Hierarchical Reinforcement Learning. - Michal Bortkiewicz; Jakub Lyskawa; Pawel Wawrzynski; Mateusz Ostaszewski; Artur Grudkowski; Bartlomiej Sobieski; Tomasz Trzcinski (ICAART (1), 2024)

Graph Vertex Embeddings: Distance, Regularization and Community Detection. - Radoslaw Nowak; Adam Malkowski; Daniel Cieslak; Piotr A. Sokól; Pawel Wawrzynski (ICCS (6), 2024)

Reinforcement Learning Meets Microeconomics: Learning to Designate Price-Dependent Supply and Demand for Automated Trading. - Lukasz Lepak; Pawel Wawrzynski (ECML/PKDD (9), 2024)

HyperInterval: Hypernetwork approach to training weight interval regions in continual learning. - Patryk Krukowski; Anna Bielawska; Kamil Ksiazek; Pawel Wawrzynski; Pawel Batorski; Przemyslaw Spurek (CoRR, 2024)

ACERAC: Efficient Reinforcement Learning in Fine Time Discretization. - Jakub Lyskawa; Pawel Wawrzynski (IEEE Trans. Neural Networks Learn. Syst., 2024)

EnEnv 1.0: Energy Grid Environment for Multi-Agent Reinforcement Learning Benchmarking. - Dominik Jacek Bogucki; Lukasz Lepak; Sonam Parashar; Bartlomiej Blachowski; Pawel Wawrzynski (AAMAS, 2025)

HINT: Hypernetwork approach to training weight interval regions in continual learning. - Patryk Krukowski; Anna Bielawska; Kamil Ksiazek; Pawel Wawrzynski; Pawel Batorski; Przemyslaw Spurek (Inf. Sci., 2025)