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Georg Hahn
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2020 – today
- 2024
- [j18]Georg Hahn, Dmitry Prokopenko, Julian Hecker
, Sharon Marie Lutz, Kristina Mullin, Leinal Sejour, Winston Hide
Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data. Briefings Bioinform. 25(4) (2024) - [j17]Georg Hahn, Sharon Marie Lutz, Julian Hecker, Dmitry Prokopenko, Michael H. Cho, Edwin K. Silverman, Scott T. Weiss, Christoph Lange:
Fast computation of the eigensystem of genomic similarity matrices. BMC Bioinform. 25(1): 43 (2024) - [i24]Kyle Henke, Elijah Pelofske, Garrett T. Kenyon, Georg Hahn:
Comparing Quantum Annealing and Spiking Neuromorphic Computing for Sampling Binary Sparse Coding QUBO Problems. CoRR abs/2405.20525 (2024) - [i23]Jingyun Qian, Georg Hahn:
An efficient heuristic for approximate maximum flow computations. CoRR abs/2409.08350 (2024) - 2023
- [j16]Sanghun Lee
A comparison between similarity matrices for principal component analysis to assess population stratification in sequenced genetic data sets. Briefings Bioinform. 24(1) (2023) - [j15]Georg Hahn, Elijah Pelofske, Hristo N. Djidjev:
Posiform planting: generating QUBO instances for benchmarking. Frontiers Comput. Sci. 5 (2023) - [j14]Elijah Pelofske
Solving larger maximum clique problems using parallel quantum annealing. Quantum Inf. Process. 22(5): 219 (2023) - [c14]Kyle Henke
Sampling binary sparse coding QUBO models using a spiking neuromorphic processor. ICONS 2023: 38:1-38:5 - [i22]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Initial state encoding via reverse quantum annealing and h-gain features. CoRR abs/2303.13748 (2023) - [i21]Kyle Henke, Elijah Pelofske, Georg Hahn, Garrett T. Kenyon:
Sampling binary sparse coding QUBO models using a spiking neuromorphic processor. CoRR abs/2306.01940 (2023) - [i20]Georg Hahn, Elijah Pelofske, Hristo N. Djidjev:
Posiform Planting: Generating QUBO Instances for Benchmarking. CoRR abs/2308.05859 (2023) - [i19]Rebecca M. Hurwitz, Georg Hahn:
Penalized Principal Component Analysis using Nesterov Smoothing. CoRR abs/2309.13838 (2023) - 2022
- [j13]Muhammad Ali Siddiqi
Improving the Security of the IEEE 802.15.6 Standard for Medical BANs. IEEE Access 10: 62953-62975 (2022) - [j12]Georg Hahn, Sanghun Lee, Dmitry Prokopenko, Jonathan Abraham, Tanya Novak, Julian Hecker, Michael H. Cho, Surender Khurana, Lindsey R. Baden, Adrienne G. Randolph, Scott T. Weiss, Christoph Lange:
Unsupervised outlier detection applied to SARS-CoV-2 nucleotide sequences can identify sequences of common variants and other variants of interest. BMC Bioinform. 23(1): 547 (2022) - [j11]Elijah Pelofske
Inferring the Dynamics of the State Evolution During Quantum Annealing. IEEE Trans. Parallel Distributed Syst. 33(2): 310-321 (2022) - [i18]Georg Hahn, Muhammad Ali Siddiqi, Said Hamdioui, Wouter A. Serdijn, Christos Strydis:
Assessing the Security of the IEEE 802.15.6 Standard for Medical BANs. CoRR abs/2201.06354 (2022) - [i17]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Solving Larger Optimization Problems Using Parallel Quantum Annealing. CoRR abs/2205.12165 (2022) - [i16]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Noise Dynamics of Quantum Annealers: Estimating the Effective Noise Using Idle Qubits. CoRR abs/2209.05648 (2022) - 2021
- [j10]Aaron Barbosa, Elijah Pelofske
Using Machine Learning for Quantum Annealing Accuracy Prediction. Algorithms 14(6): 187 (2021) - [j9]Georg Hahn
A fast and efficient smoothing approach to Lasso regression and an application in statistical genetics: polygenic risk scores for chronic obstructive pulmonary disease (COPD). Stat. Comput. 31(3): 35 (2021) - [j8]Elijah Pelofske
Decomposition Algorithms for Solving NP-hard Problems on a Quantum Annealer. J. Signal Process. Syst. 93(4): 405-420 (2021) - [c13]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Reducing quantum annealing biases for solving the graph partitioning problem. CF 2021: 133-139 - [c12]Elijah Pelofske
Boolean Hierarchical Tucker Networks on Quantum Annealers. LSSC 2021: 351-358 - [i15]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Reducing quantum annealing biases for solving the graph partitioning problem. CoRR abs/2103.04963 (2021) - [i14]Elijah Pelofske, Georg Hahn, Daniel O'Malley, Hristo N. Djidjev, Boian S. Alexandrov:
Boolean Hierarchical Tucker Networks on Quantum Annealers. CoRR abs/2103.07399 (2021) - [i13]Aaron Barbosa, Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Using machine learning for quantum annealing accuracy prediction. CoRR abs/2106.00065 (2021) - [i12]Elijah Pelofske, Georg Hahn, Daniel O'Malley, Hristo N. Djidjev, Boian S. Alexandrov:
Quantum Annealing Algorithms for Boolean Tensor Networks. CoRR abs/2107.13659 (2021) - [i11]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Parallel Quantum Annealing. CoRR abs/2111.05995 (2021) - 2020
- [j7]Dong Ding
A simple method for implementing Monte Carlo tests. Comput. Stat. 35(3): 1373-1392 (2020) - [j6]Georg Hahn
Optimal allocation of Monte Carlo simulations to multiple hypothesis tests. Stat. Comput. 30(3): 571-586 (2020) - [j5]Georg Hahn
BayesProject: Fast computation of a projection direction for multivariate changepoint detection. Stat. Comput. 30(6): 1691-1705 (2020) - [c11]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev
Advanced unembedding techniques for quantum annealers. ICRC 2020: 34-41 - [c10]Aaron Barbosa, Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Optimizing Embedding-Related Quantum Annealing Parameters for Reducing Hardware Bias. PAAP 2020: 162-173 - [c9]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Advanced anneal paths for improved quantum annealing. QCE 2020: 256-266 - [i10]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Advanced anneal paths for improved quantum annealing. CoRR abs/2009.05008 (2020) - [i9]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Advanced unembedding techniques for quantum annealers. CoRR abs/2009.05028 (2020) - [i8]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Inferring the Dynamics of the State Evolution During Quantum Annealing. CoRR abs/2009.06387 (2020) - [i7]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Decomposition algorithms for solving NP-hard problems on a quantum annealer. CoRR abs/2009.06726 (2020) - [i6]Aaron Barbosa, Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Optimizing embedding-related quantum annealing parameters for reducing hardware bias. CoRR abs/2011.00719 (2020)
2010 – 2019
- 2019
- [j4]Hristo N. Djidjev
Using Graph Partitioning for Scalable Distributed Quantum Molecular Dynamics. Algorithms 12(9): 187 (2019) - [j3]Guillaume Chapuis, Hristo N. Djidjev
Finding Maximum Cliques on the D-Wave Quantum Annealer. J. Signal Process. Syst. 91(3-4): 363-377 (2019) - [c8]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev
Solving large minimum vertex cover problems on a quantum annealer. CF 2019: 76-84 - [c7]Georg Hahn, Sharon Marie Lutz, Julian Hecker, Dmitry Prokopenko, Christoph Lange:
Local and Global Stratification Analysis in Whole Genome Sequencing (WGS) Studies Using LocStra. ICCABS 2019: 159-170 - [c6]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Optimizing the Spin Reversal Transform on the D-Wave 2000Q. ICRC 2019: 63-70 - [c5]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Peering Into the Anneal Process of a Quantum Annealer. PDCAT 2019: 184-189 - [i5]Elijah Pelofske, Georg Hahn
Solving large Maximum Clique problems on a quantum annealer. CoRR abs/1901.07657 (2019) - [i4]Elijah Pelofske, Georg Hahn
Solving large Minimum Vertex Cover problems on a quantum annealer. CoRR abs/1904.00051 (2019) - [i3]Elijah Pelofske, Georg Hahn
Optimizing the spin reversal transform on the D-Wave 2000Q. CoRR abs/1906.10955 (2019) - [i2]Elijah Pelofske, Georg Hahn, Hristo N. Djidjev:
Peering into the Anneal Process of a Quantum Annealer. CoRR abs/1908.02691 (2019) - 2018
- [i1]Georg Hahn, Hristo N. Djidjev:
Reducing Binary Quadratic Forms for More Scalable Quantum Annealing. CoRR abs/1801.08652 (2018) - 2017
- [j2]Axel Gandy
QuickMMCTest: quick multiple Monte Carlo testing. Stat. Comput. 27(3): 823-832 (2017) - [j1]Purnima Ghale
Task-based Parallel Computation of the Density Matrix in Quantum-based Molecular Dynamics using Graph Partitioning. SIAM J. Sci. Comput. 39(6) (2017) - [c4]Guillaume Chapuis, Hristo N. Djidjev
Finding Maximum Cliques on a Quantum Annealer. Conf. Computing Frontiers 2017: 63-70 - [c3]Georg Hahn, Hristo N. Djidjev
Reducing Binary Quadratic Forms for More Scalable Quantum Annealing. ICRC 2017: 1-8 - [c2]Elijah Pelofske, Georg Hahn
Solving Large Maximum Clique Problems on a Quantum Annealer. QTOP@NetSys 2017: 123-135 - 2016
- [c1]Hristo N. Djidjev, Georg Hahn
Graph Partitioning Methods for Fast Parallel Quantum Molecular Dynamics. CSC 2016: 42-51
Coauthor Index
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