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Yaroslav Koshka
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2020 – today
- 2023
- [c3]Kenzie Ellenberger, Dylan Couch, Jeffrey Greer, Noah Gregory, Luis Sanchez, Kaleb Love, Yaroslav Koshka, Samee U. Khan:
Quantum Task Mapping for Distributed Heterogeneous Computing Systems. QCE 2023: 387-388 - 2022
- [j5]Vivek Dixit
, Raja Selvarajan, Tamer Aldwairi
Training a Quantum Annealing Based Restricted Boltzmann Machine on Cybersecurity Data. IEEE Trans. Emerg. Top. Comput. Intell. 6(3): 417-428 (2022) - 2021
- [j4]Yaroslav Koshka
Comparison of Use of a 2000 Qubit D-Wave Quantum Annealer and MCMC for Sampling, Image Reconstruction, and Classification. IEEE Trans. Emerg. Top. Comput. Intell. 5(1): 119-129 (2021) - 2020
- [j3]Yaroslav Koshka
Comparison of D-Wave Quantum Annealing and Classical Simulated Annealing for Local Minima Determination. IEEE J. Sel. Areas Inf. Theory 1(2): 515-525 (2020) - [j2]Yaroslav Koshka
Toward sampling from undirected probabilistic graphical models using a D-Wave quantum annealer. Quantum Inf. Process. 19(9): 353 (2020)
2010 – 2019
- 2019
- [i2]Yaroslav Koshka, Mark A. Novotny:
Towards Sampling from Nondirected Probabilistic Graphical models using a D-Wave Quantum Annealer. CoRR abs/1905.00159 (2019) - [i1]Yaroslav Koshka, Mark A. Novotny:
Comparison of D-Wave Quantum Annealing and Classical Simulated Annealing for Local Minima Determination. CoRR abs/1911.03338 (2019) - 2018
- [c2]Yaroslav Koshka, Mark A. Novotny:
2000 Qubit D-Wave Quantum Computer Replacing MCMC for RBM Image Reconstruction and Classification. IJCNN 2018: 1-8 - 2017
- [j1]Yaroslav Koshka
Determination of the Lowest-Energy States for the Model Distribution of Trained Restricted Boltzmann Machines Using a 1000 Qubit D-Wave 2X Quantum Computer. Neural Comput. 29(7): 1815-1837 (2017) - 2016
- [c1]Yaroslav Koshka
Empirical investigation of the low temperature energy function of the Restricted Boltzmann Machine using a 1000 qubit D-Wave 2X. IJCNN 2016: 1948-1954
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