Mateusz Ostaszewski

According to our database, Mateusz Ostaszewski authored at least 23 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A Case for Validation Buffer in Pessimistic Actor-Critic.

Michal Nauman, Mateusz Ostaszewski, Marek Cygan

CoRR, 2024

Bigger, Regularized, Optimistic: scaling for compute and sample efficient continuous control.

Michal Nauman, Mateusz Ostaszewski, Krzysztof Jankowski, Piotr Milos, Marek Cygan

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem.

Maciej Wolczyk, Bartlomiej Cupial, Mateusz Ostaszewski, Michal Bortkiewicz, Michal Zajac, Razvan Pascanu, Lukasz Kucinski, Piotr Milos

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning.

Michal Nauman, Michal Bortkiewicz, Piotr Milos, Tomasz Trzcinski, Mateusz Ostaszewski, Marek Cygan

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Curriculum reinforcement learning for quantum architecture search under hardware errors.

Yash J. Patel, Akash Kundu, Mateusz Ostaszewski, Xavier Bonet-Monroig, Vedran Dunjko, Onur Danaci

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Subgoal Reachability in Goal Conditioned Hierarchical Reinforcement Learning.

Michal Bortkiewicz, Jakub Lyskawa, Pawel Wawrzynski, Mateusz Ostaszewski, Artur Grudkowski, Bartlomiej Sobieski, Tomasz Trzcinski

Proceedings of the 16th International Conference on Agents and Artificial Intelligence, 2024

2023

On consequences of finetuning on data with highly discriminative features.

Wojciech Masarczyk, Tomasz Trzcinski, Mateusz Ostaszewski

CoRR, 2023

Enhancing variational quantum state diagonalization using reinforcement learning techniques.

Akash Kundu, Przemyslaw Bedelek, Mateusz Ostaszewski, Onur Danaci, Yash J. Patel, Vedran Dunjko, Jaroslaw Adam Miszczak

CoRR, 2023

The Tunnel Effect: Building Data Representations in Deep Neural Networks.

Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Milos, Tomasz Trzcinski

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

The Effectiveness of World Models for Continual Reinforcement Learning.

Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos

Proceedings of the Conference on Lifelong Learning Agents, 2023

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

Reinforcement learning with experience replay and adaptation of action dispersion.

Pawel Wawrzynski, Wojciech Masarczyk, Mateusz Ostaszewski

CoRR, 2022

2021

Structure optimization for parameterized quantum circuits.

Mateusz Ostaszewski, Edward Grant, Marcello Benedetti

Quantum, 2021

Reinforcement learning for optimization of variational quantum circuit architectures.

Mateusz Ostaszewski, Lea M. Trenkwalder, Wojciech Masarczyk, Eleanor Scerri, Vedran Dunjko

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling.

Wojciech Masarczyk, Przemyslaw Glomb, Bartosz Grabowski, Mateusz Ostaszewski

Remote. Sens., 2020

2019

Approximation of quantum control correction scheme using deep neural networks.

Mateusz Ostaszewski, J. A. Miszczak, Leonardo Banchi, Przemyslaw Sadowski

Quantum Inf. Process., 2019

QSWalk.jl: Julia package for quantum stochastic walks analysis.

Adam Glos, Jaroslaw Adam Miszczak, Mateusz Ostaszewski

Comput. Phys. Commun., 2019

Effective transfer learning for hyperspectral image classification with deep convolutional neural networks.

Wojciech Masarczyk, Przemyslaw Glomb, Bartosz Grabowski, Mateusz Ostaszewski

CoRR, 2019

2018

Properties of quantum stochastic walks from the asymptotic scaling exponent.

Krzysztof Domino, Adam Glos, Mateusz Ostaszewski, Lukasz Pawela, Przemyslaw Sadowski

Quantum Inf. Comput., 2018

Geometrical versus time-series representation of data in quantum control learning.

Mateusz Ostaszewski, Jaroslaw Adam Miszczak, Przemyslaw Sadowski

CoRR, 2018

2017

Superdiffusive quantum stochastic walk definable on arbitrary directed graph.

Krzysztof Domino, Adam Glos, Mateusz Ostaszewski

Quantum Inf. Comput., 2017

2015

Lively quantum walks on cycles.

Przemyslaw Sadowski, Jaroslaw Adam Miszczak, Mateusz Ostaszewski

CoRR, 2015

Quantum image classification using principal component analysis.

Mateusz Ostaszewski, Przemyslaw Sadowski, Piotr Gawron

CoRR, 2015