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Mateusz Ostaszewski
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Year
An initialization strategy for addressing barren plateaus in parametrized quantum circuits
E Grant, L Wossnig, M Ostaszewski, M Benedetti
Quantum 3, 214, 2019
3632019
Structure optimization for parameterized quantum circuits
M Ostaszewski, E Grant, M Benedetti
Quantum 5, 391, 2021
210*2021
Reinforcement learning for optimization of variational quantum circuit architectures
M Ostaszewski, LM Trenkwalder, W Masarczyk, E Scerri, V Dunjko
Advances in Neural Information Processing Systems 34, 18182-18194, 2021
852021
Effective training of deep convolutional neural networks for hyperspectral image classification through artificial labeling
W Masarczyk, P Głomb, B Grabowski, M Ostaszewski
Remote Sensing 12 (16), 2653, 2020
24*2020
Quantum image classification using principal component analysis
M Ostaszewski, P Sadowski, P Gawron
Theoretical and Applied Informatics 27 (1), 1-12, 2015
202015
Approximation of quantum control correction scheme using deep neural networks
M Ostaszewski, JA Miszczak, L Banchi, P Sadowski
Quantum Information Processing 18 (5), 126, 2019
182019
Lively quantum walks on cycles
P Sadowski, JA Miszczak, M Ostaszewski
Journal of Physics A: Mathematical and Theoretical 49 (37), 375302, 2016
162016
QSWalk. jl: Julia package for quantum stochastic walks analysis
A Glos, JA Miszczak, M Ostaszewski
Computer Physics Communications 235, 414-421, 2019
122019
Superdiffusive quantum stochastic walk definable of arbitrary directed graph
K Domino, A Glos, M Ostaszewski
QUANTUM INFORMATION & COMPUTATION 17 (11-12), 973-986, 2017
11*2017
Properties of quantum stochastic walks from the asymptotic scaling exponent
K Domino, A Glos, M Ostaszewski, Ł Pawela, P Sadowski
Quantum Information & Computation 18 (3-4), 181–197, 2016
11*2016
Limiting properties of stochastic quantum walks on directed graphs
A Glos, JA Miszczak, M Ostaszewski
Journal of Physics A: Mathematical and Theoretical 51 (3), 035304, 2017
92017
The Effectiveness of World Models for Continual Reinforcement Learning
S Kessler, M Ostaszewski, MP Bortkiewicz, M Żarski, M Wolczyk, ...
Conference on Lifelong Learning Agents, 184-204, 2023
8*2023
Geometrical versus time-series representation of data in quantum control learning
M Ostaszewski, JA Miszczak, P Sadowski
Journal of Physics A: Mathematical and Theoretical 53 (19), 195301, 2020
5*2020
The Tunnel Effect: Building Data Representations in Deep Neural Networks
W Masarczyk, M Ostaszewski, E Imani, R Pascanu, P Miłoś, T Trzciński
arXiv preprint arXiv:2305.19753, 2023
32023
Curriculum reinforcement learning for quantum architecture search under hardware errors
YJ Patel, A Kundu, M Ostaszewski, X Bonet-Monroig, V Dunjko, O Danaci
arXiv preprint arXiv:2402.03500, 2024
12024
Enhancing variational quantum state diagonalization using reinforcement learning techniques
A Kundu, P Bedełek, M Ostaszewski, O Danaci, YJ Patel, V Dunjko, ...
New Journal of Physics 26 (1), 013034, 2024
12024
Curriculum reinforcement learning for optimization of variational quantum circuit architectures
M Ostaszewski, W Masarczyk, L Trenkwalder, E Scerri, V Dunjko
NeurIPS 2020, Third Workshop on Machine Learning and the Physical Sciences, 2020
12020
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
M Wołczyk, B Cupiał, M Ostaszewski, M Bortkiewicz, M Zając, R Pascanu, ...
arXiv preprint arXiv:2402.02868, 2024
2024
On consequences of finetuning on data with highly discriminative features
W Masarczyk, T Trzciński, M Ostaszewski
arXiv preprint arXiv:2310.19537, 2023
2023
Emergency action termination for immediate reaction in hierarchical reinforcement learning
M Bortkiewicz, J Łyskawa, P Wawrzyński, M Ostaszewski, A Grudkowski, ...
arXiv preprint arXiv:2211.06351, 2022
2022
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Articles 1–20