E Alwadee, X Sun, Y Qin, FC Langbein. LATUP-Net: A Lightweight 3D Attention U-Net with Parallel Convolutions for Brain Tumor Segmentation. Preprint, 2024. [arxiv:2404.05911] [PDF]
Quantum
S. P. O’Neil, C. A. Weidner, E. A. Jonckheere, F. C. Langbein, S. G. Schirmer. Robustness of Dynamic Quantum Control: Differential Sensitivity Bounds. Preprint, 2023. [arXiv:2401.00301] [PDF]
Robustness of Dynamic Quantum Control: Differential Sensitivity Bounds
C. A. Weidner, E. A. Reed, J. Monroe, S. O’Neil, E. Maas, E. A. Jonckheere, F. C. Langbein, S. G. Schirmer. Robust Quantum Control in Closed and Open Systems: Theory and Practice. Preprint, 2023. [arXiv:2401.00294] [PDF]
Robust Quantum Control in Closed and Open Systems: Theory and ...
Finding and Characterising Robust Quantum Controls. Faculti interview with Frank Langbein on robust quantum control, 25th May 2023. [URL: https://faculti.net/finding-and-characterising-robust-quantum-controls/]
Interview – Finding and Characterising Robust Quantum Controls
Zien Ma, Oktay Karakus, Sophie Shermer, Frank Langbein. Quantification of Metabolites in Magnetic Resonance Spectra with Deep Learning: Insights on Simulated and Real Data. Presentation at the One Day Meeting: Synthetic Data for Machine Learning, The British Machine Vision Association and Society for Pattern Recognition, Wednesday 8 November 2023. [PDF:abstract]
Quantification of Metabolites in Magnetic Resonance Spectra with Deep Learning ...
E Jonckheere, SG Schirmer, FC Langbein, CA Weidner, S O’Neil. Disturbance-agnostic robust performance with structured uncertainties and initial state error in classical versus quantum oscillatory systems. Preprint, 2023. [arXiv:2305.03918] [PDF]
Disturbance-agnostic robust performance with structured uncertainties and initial state error ...
FC Langbein. Control and Machine Learning for Magnetic Resonance Spectroscopy. Keynote talk, Frontiers of Intelligent Computing: Theory and Applications (FICTA), 11-12 April 2023. [Slides]
Control and Machine Learning for Magnetic Resonance Spectroscopy
I Khalid, CA Weider, EA Jonckheere, SG Shermer, FC Langbein. Sample-efficient Model-based Reinforcement Learning for Quantum Control. Phys. Rev. Research 5, 043002, 2023. [DOI:10.1103/PhysRevResearch.5.043002] [arXiv:2304.09718] [PDF]
Sample-efficient Model-based Reinforcement Learning for Quantum Control
Irtaza Khalid, Carrie Weidner, S.G. Schirmer, Edmond Jonckheere, Frank C. Langbein. Sample-efficient Model-based Reinforcement Learning for Quantum Control. Poster, BQIT:23, 2023. [PDF:poster]
BQIT:23 – Sample-efficient Model-based Reinforcement Learning for Quantum Control
SP O’Neil, I Khalid, AA Rompokmos, CA Weidner, FC Langbein, S Schirmer, EA Jonckmheere. Analyzing and Unifying Robustness Measures for Excitation Transfer Control in Spin Networks. IEEE Control Systems Letters, 7:1783-1788, 2023. Also accepted for presentation at the IEEE Conf. Decision and Control (CDC) 2023. [DOI:10.1109/LCSYS.2023.3279797] [arXiv:2303.09518] [PDF]
Analyzing and Unifying Robustness Measures for Excitation Transfer Control in ...
FC Langbein, SP O’Neil, SG Shermer. Data – Energy Landscape Controllers for XX Spin Rings. Dataset, 2023. [https://qyber.black/spinnet/data-elc-xx-rings] FC Langbein, SP O’Neil, SG Shermer. Results – Energy Landscape Controllers for XX Spin Rings – Robustness. Dataset, 2023. [https://qyber.black/spinnet/results-elc-xx-rings-robustness] SP O’Neil, FC Langbein, SG Shermer. Robustness of Energy Landscape Controllers for […]
Energy Landscape Controllers for XX Spin Rings
S O’Neil, FC Langbein, E Jonckheere, SG Shermer. Robustness of Energy Landscape Control to Dephasing. Research Directions: Quantum Technologies, 1, E13, 2023. [DOI:10.1017/qut.2023.6] [arXiv:2303.05649] [PDF]