Volgen
Mateusz Ostaszewski
Mateusz Ostaszewski
Warsaw University of Technology
Geverifieerd e-mailadres voor pw.edu.pl
Titel
Geciteerd door
Geciteerd door
Jaar
An initialization strategy for addressing barren plateaus in parametrized quantum circuits
E Grant, L Wossnig, M Ostaszewski, M Benedetti
Quantum 3, 214, 2019
4962019
Structure optimization for parameterized quantum circuits
M Ostaszewski, E Grant, M Benedetti
Quantum 5, 391, 2021
267*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
1582021
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
28*2020
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
232019
Quantum image classification using principal component analysis
M Ostaszewski, P Sadowski, P Gawron
Theoretical and Applied Informatics 27 (1), 1-12, 2015
212015
Curriculum reinforcement learning for quantum architecture search under hardware errors
YJ Patel, A Kundu, M Ostaszewski, X Bonet-Monroig, V Dunjko, O Danaci
The Twelfth International Conference on Learning Representations., 2024
182024
Lively quantum walks on cycles
P Sadowski, JA Miszczak, M Ostaszewski
Journal of Physics A: Mathematical and Theoretical 49 (37), 375302, 2016
182016
The Tunnel Effect: Building Data Representations in Deep Neural Networks
W Masarczyk, M Ostaszewski, E Imani, R Pascanu, P Miłoś, T Trzciński
Advances in Neural Information Processing Systems 36 (2024)., 2023
172023
Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning
M Nauman, M Bortkiewicz, P Miłoś, T Trzciński, M Ostaszewski, M Cygan
ICML 2024, 2024
162024
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
14*2023
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
M Wołczyk, B Cupiał, M Ostaszewski, M Bortkiewicz, M Zając, R Pascanu, ...
ICML 2024 (Spotlight), 2024
13*2024
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
13*2024
QSWalk. jl: Julia package for quantum stochastic walks analysis
A Glos, JA Miszczak, M Ostaszewski
Computer Physics Communications 235, 414-421, 2019
132019
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
Bigger, Regularized, Optimistic: scaling for compute and sample-efficient continuous control
M Nauman, M Ostaszewski, K Jankowski, P Miłoś, M Cygan
NeurIPS 2024 (Spotlight), 2024
102024
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
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
Learning Continually by Spectral Regularization
A Lewandowski, M Bortkiewicz, S Kumar, A György, D Schuurmans, ...
arXiv preprint arXiv:2406.06811, 2024
42024
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Artikelen 1–20