Publikacje
Found 15 results
Filters: Autor is Mateusz Ostaszewski [Clear All Filters]
Enhancing quantum variational state diagonalization using reinforcement learning techniques. New Journal of Physics. 26
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2024. The Effectiveness of World Models for Continual Reinforcement Learning. Conference on Lifelong Learning Agents.
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2021. .
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Effective Training of Deep Convolutional Neural Networks for Hyperspectral Image Classification through Artificial Labeling. Remote Sensing. 12(16)
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2020. Geometrical versus time-series representation of data in quantum control learning. Journal of Physics A: Mathematical and Theoretical. 53(19)
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2020. Approximation of quantum control correction scheme using deep neural networks. Quantum Information Processing. 18
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2019. An initialization strategy for addressing barren plateaus in parametrized quantum circuits. Quantum. 3
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2019. QSWalk. jl: Julia package for quantum stochastic walks analysis. Computer Physics Communications. 235
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2019. Limiting properties of stochastic quantum walks on directed graphs. Journal of Physics A: Mathematical and Theoretical. 51(3)
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2018. Properties of quantum stochastic walks from the asymptotic scaling exponent. Quantum Information and Computation. 18(3&4)
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2018. Superdiffusive quantum stochastic walk definable on arbitrary directed graph. Quantum Information & Computation. 17(11&12)
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2017. Lively quantum walks on cycles. J. Phys. A: Math. Theor.. 49:375302.
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2016. Quantum image classification using principal component analysis. Theoretical and Applied Informatics. 27(1)
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2015.