default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDPawel Wawrzynski
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[j8]Jakub Lyskawa
, Pawel Wawrzynski:
ACERAC: Efficient Reinforcement Learning in Fine Time Discretization. IEEE Trans. Neural Networks Learn. Syst. 35(2): 2719-2731 (2024)- [c28]Michal Bortkiewicz, Jakub Lyskawa, Pawel Wawrzynski, Mateusz Ostaszewski, Artur Grudkowski, Bartlomiej Sobieski, Tomasz Trzcinski:
Subgoal Reachability in Goal Conditioned Hierarchical Reinforcement Learning. ICAART (1) 2024: 221-230 - [c27]Radoslaw Nowak, Adam Malkowski, Daniel Cieslak, Piotr Sokól, Pawel Wawrzynski:
Graph Vertex Embeddings: Distance, Regularization and Community Detection. ICCS (6) 2024: 43-57 - [c26]Lukasz Lepak, Pawel Wawrzynski:
Reinforcement Learning Meets Microeconomics: Learning to Designate Price-Dependent Supply and Demand for Automated Trading. ECML/PKDD (9) 2024: 368-384 - [i15]Radoslaw Nowak, Adam Malkowski, Daniel Cieslak, Piotr Sokól, Pawel Wawrzynski:
Graph Vertex Embeddings: Distance, Regularization and Community Detection. CoRR abs/2404.10784 (2024) - [i14]Patryk Krukowski, Anna Bielawska, Kamil Ksiazek, Pawel Wawrzynski, Pawel Batorski, Przemyslaw Spurek:
HyperInterval: Hypernetwork approach to training weight interval regions in continual learning. CoRR abs/2405.15444 (2024) - 2023
- [c25]Jakub Lyskawa, Pawel Wawrzynski:
Actor-Critic with Variable Time Discretization via Sustained Actions. ICONIP (1) 2023: 476-489 - [c24]Lukasz Neumann, Lukasz Lepak, Pawel Wawrzynski:
Least Redundant Gated Recurrent Neural Network. IJCNN 2023: 1-10 - [i13]Lukasz Lepak, Pawel Wawrzynski:
Reinforcement learning for optimization of energy trading strategy. CoRR abs/2303.16266 (2023) - [i12]Jakub Lyskawa, Pawel Wawrzynski:
Actor-Critic with variable time discretization via sustained actions. CoRR abs/2308.04299 (2023) - 2022
- [j7]Wojciech Masarczyk, Pawel Wawrzynski, Daniel Marczak, Kamil Deja, Tomasz Trzcinski:
Logarithmic Continual Learning. IEEE Access 10: 117001-117010 (2022) - [c23]Grzegorz Rypesc, Lukasz Lepak, Pawel Wawrzynski:
Reinforcement Learning for on-line Sequence Transformation. FedCSIS 2022: 133-139 - [c22]Adam Malkowski, Jakub Grzechocinski, Pawel Wawrzynski:
ReGAE: Graph Autoencoder Based on Recursive Neural Networks. ICONIP (4) 2022: 263-274 - [c21]Kamil Deja, Pawel Wawrzynski, Wojciech Masarczyk, Daniel Marczak, Tomasz Trzcinski:
Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning. IJCAI 2022: 2902-2908 - [i11]Wojciech Masarczyk, Pawel Wawrzynski, Daniel Marczak, Kamil Deja, Tomasz Trzcinski:
Logarithmic Continual Learning. CoRR abs/2201.06534 (2022) - [i10]Adam Malkowski, Jakub Grzechocinski, Pawel Wawrzynski:
Graph autoencoder with constant dimensional latent space. CoRR abs/2201.12165 (2022) - [i9]Pawel Wawrzynski, Wojciech Masarczyk, Mateusz Ostaszewski:
Reinforcement learning with experience replay and adaptation of action dispersion. CoRR abs/2208.00156 (2022) - [i8]Michal Bortkiewicz, Jakub Lyskawa, Pawel Wawrzynski, Mateusz Ostaszewski, Artur Grudkowski, Tomasz Trzcinski:
Emergency action termination for immediate reaction in hierarchical reinforcement learning. CoRR abs/2211.06351 (2022) - 2021
- [c20]Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski:
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. IJCNN 2021: 1-8 - [i7]Pawel Wawrzynski, Jakub Lyskawa:
ACERAC: Efficient reinforcement learning in fine time discretization. CoRR abs/2104.04004 (2021) - [i6]Lukasz Neumann, Pawel Wawrzynski:
Deep Memory Update. CoRR abs/2105.14092 (2021) - [i5]Grzegorz Rypesc, Lukasz Lepak, Pawel Wawrzynski:
Reinforcement Learning for on-line Sequence Transformation. CoRR abs/2105.14097 (2021) - [i4]Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski:
Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning. CoRR abs/2106.12196 (2021) - 2020
- [c19]Marcin Szulc, Jakub Lyskawa, Pawel Wawrzynski:
A Framework for Reinforcement Learning with Autocorrelated Actions. ICONIP (2) 2020: 90-101 - [c18]Karol Cheinski, Pawel Wawrzynski:
DCT-Conv: Coding filters in convolutional networks with Discrete Cosine Transform. IJCNN 2020: 1-6 - [c17]Pawel Wawrzynski, Pawel Zawistowski, Lukasz Lepak:
Automatic hyperparameter tuning in on-line learning: Classic Momentum and ADAM. IJCNN 2020: 1-8 - [i3]Karol Cheinski, Pawel Wawrzynski:
DCT-Conv: Coding filters in convolutional networks with Discrete Cosine Transform. CoRR abs/2001.08517 (2020) - [i2]Marcin Szulc, Jakub Lyskawa, Pawel Wawrzynski:
A framework for reinforcement learning with autocorrelated actions. CoRR abs/2009.04777 (2020) - [i1]Kamil Deja, Pawel Wawrzynski, Daniel Marczak, Wojciech Masarczyk, Tomasz Trzcinski:
BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. CoRR abs/2011.14960 (2020)
2010 – 2019
- 2019
- [j6]Lukasz Neumann, Robert M. Nowak, Rafal Okuniewski, Pawel Wawrzynski:
Machine Learning-Based Predictions of Customers' Decisions in Car Insurance. Appl. Artif. Intell. 33(9): 817-828 (2019) - [c16]Pawel Wawrzynski:
Efficient on-line learning with diagonal approximation of loss function Hessian. IJCNN 2019: 1-8 - [c15]Andrea Zanetti, Alberto Testolin, Marco Zorzi, Pawel Wawrzynski:
Numerosity Representation in InfoGAN: An Empirical Study. IWANN (2) 2019: 49-60 - 2017
- [j5]Pawel Wawrzynski:
ASD+M: Automatic parameter tuning in stochastic optimization and on-line learning. Neural Networks 96: 1-10 (2017) - [c14]Pawel Wawrzynski:
Parameter-Free On-line Deep Learning. AUTOMATION 2017: 543-553 - 2015
- [j4]Pawel Wawrzynski, Jakub Mozaryn, Jan Klimaszewski:
Robust estimation of walking robots velocity and tilt using proprioceptive sensors data fusion. Robotics Auton. Syst. 66: 44-54 (2015) - [c13]Pawel Wawrzynski:
Robot's velocity and tilt estimation through computationally efficient fusion of proprioceptive sensors readouts. MMAR 2015: 738-743 - [c12]Michal Majczak, Pawel Wawrzynski:
Comparison of two efficient control strategies for two-wheeled balancing robot. MMAR 2015: 744-749 - 2014
- [j3]Pawel Wawrzynski:
Reinforcement Learning with Experience Replay for Model-Free Humanoid Walking Optimization. Int. J. Humanoid Robotics 11(3) (2014) - [c11]Jakub Mozaryn, Jan Klimaszewski, Pawel Kolodziejczyk, Dariusz Swieczkowski-Feiz, Pawel Wawrzynski:
Design process and experimental verification of the quadruped robot wave gait. MMAR 2014: 206-211 - 2013
- [c10]Bartosz Papis, Pawel Wawrzynski:
dotRL: A platform for rapid Reinforcement Learning methods development and validation. FedCSIS 2013: 129-136 - [c9]Piotr Suszynski, Pawel Wawrzynski:
Learning population of spiking neural networks with perturbation of conductances. IJCNN 2013: 1-6 - [c8]Pawel Wawrzynski, Jakub Mozaryn, Jan Klimaszewski:
Robust velocity estimation for legged robot using on-board sensors data fusion. MMAR 2013: 717-722 - 2012
- [c7]Pawel Wawrzynski:
Autonomous Reinforcement Learning with Experience Replay for Humanoid Gait Optimization. INNS-WC 2012: 205-211 - 2011
- [j2]Pawel Wawrzynski, Bartosz Papis:
Fixed point method for autonomous on-line neural network training. Neurocomputing 74(17): 2893-2905 (2011) - 2010
- [c6]Pawel Wawrzynski:
Fixed point method of step-size estimation for on-line neural network training. IJCNN 2010: 1-6
2000 – 2009
- 2009
- [j1]Pawel Wawrzynski:
Real-time reinforcement learning by sequential Actor-Critics and experience replay. Neural Networks 22(10): 1484-1497 (2009) - [c5]Pawel Wawrzynski:
A Cat-Like Robot Real-Time Learning to Run. ICANNGA 2009: 380-390 - 2008
- [c4]Pawel Wawrzynski, Jaroslaw Arabas, Pawel Cichosz:
Predictive Control for Artificial Intelligence in Computer Games. ICAISC 2008: 1137-1148 - 2007
- [c3]Pawel Wawrzynski:
Reinforcement Learning in Fine Time Discretization. ICANNGA (1) 2007: 470-479 - 2005
- [c2]Pawel Wawrzynski, Andrzej Pacut:
Reinforcement Learning in Quasi-Continuous Time. CIMCA/IAWTIC 2005: 1031-1036 - 2004
- [c1]Pawel Wawrzynski, Andrzej Pacut:
Intensive versus Non-intensive Actor-Critic Reinforcement Learning Algorithms. ICAISC 2004: 934-941
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 21:19 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
