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Brian T. Kirby
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Journal Articles
- 2023
- [j6]Manon P. Bart, Nicholas J. Savino, Paras Regmi, Lior Cohen, Haleh Safavi, Harry C. Shaw, Sanjaya Lohani, Thomas A. Searles, Brian T. Kirby, Hwang Lee, Ryan T. Glasser:
Deep learning for enhanced free-space optical communications. Mach. Learn. Sci. Technol. 4(4): 45046 (2023) - [j5]Sanjaya Lohani, Sangita Regmi, Joseph M. Lukens, Ryan T. Glasser, Thomas A. Searles, Brian T. Kirby:
Dimension-adaptive machine learning-based quantum state reconstruction. Quantum Mach. Intell. 5(1): 1-10 (2023) - 2022
- [j4]Sanjaya Lohani, Joseph M. Lukens, Ryan T. Glasser, Thomas A. Searles, Brian T. Kirby:
Data-centric machine learning in quantum information science. Mach. Learn. Sci. Technol. 3(4): 4 (2022) - 2021
- [j3]Onur Danaci, Sanjaya Lohani, Brian T. Kirby, Ryan T. Glasser:
Machine learning pipeline for quantum state estimation with incomplete measurements. Mach. Learn. Sci. Technol. 2(3): 35014 (2021) - 2020
- [j2]Sanjaya Lohani, Brian T. Kirby, Michael Brodsky, Onur Danaci, Ryan T. Glasser:
Machine learning assisted quantum state estimation. Mach. Learn. Sci. Technol. 1(3): 35007 (2020) - 2009
- [j1]Seth Copen Goldstein, Todd C. Mowry, Jason Campbell, Michael P. Ashley-Rollman, Michael DeRosa, Stanislav Funiak, James F. Hoburg, Mustafa Emre Karagozler, Brian T. Kirby, Peter Lee, Padmanabhan Pillai, James Robert Reid, Daniel D. Stancil, Michael Philetus Weller:
Beyond Audio and Video: Using Claytronics to Enable Pario. AI Mag. 30(2): 29-45 (2009)
Conference and Workshop Papers
- 2023
- [c8]Dashiell L. P. Vitullo, Trevor Cook, Daniel E. Jones, Lisa M. Scott, Brian T. Kirby:
Computational Simulation Framework for Tactical Quantum Network Applications. MILCOM 2023: 100-102 - 2022
- [c7]Changjia Chen, Calvin Xu, Arash Riazi, Eric Y. Zhu, Alexander Greenwood, Alexey V. Gladyshev, Peter G. Kazansky, Brian T. Kirby, Li Qian:
Telecom-band Hyperentangled Photon Pairs from a Fiber-based Source. OFC 2022: 1-3 - 2018
- [c6]Daniel E. Jones, Brian T. Kirby, Michael Brodsky:
Polarization Dependent Loss in Optical Fibers - Does it Help or Ruin Photon Entanglement Distribution? OFC 2018: 1-3 - 2011
- [c5]Brian T. Kirby, Michael P. Ashley-Rollman, Seth Copen Goldstein:
Blinky blocks: a physical ensemble programming platform. CHI Extended Abstracts 2011: 1111-1116 - 2009
- [c4]Michael Philetus Weller, Brian T. Kirby, H. Benjamin Brown, Mark D. Gross, Seth Copen Goldstein:
Design of prismatic cube modules for convex corner traversal in 3D. IROS 2009: 1490-1495 - 2007
- [c3]Brian T. Kirby, Burak Aksak, Jason Campbell, James F. Hoburg, Todd C. Mowry, Padmanabhan Pillai, Seth Copen Goldstein:
A modular robotic system using magnetic force effectors. IROS 2007: 2787-2793 - 2005
- [c2]Brian T. Kirby, Jason Campbell, Burak Aksak, Padmanabhan Pillai, James F. Hoburg, Todd C. Mowry, Seth Copen Goldstein:
Catoms: Moving Robots Without Moving Parts. AAAI 2005: 1730-1731 - [c1]Burak Aksak, Preethi Srinivas Bhat, Jason Campbell, Michael DeRosa, Stanislav Funiak, Phillip B. Gibbons, Seth Copen Goldstein, Carlos Guestrin, Ashish Gupta, Casey Helfrich, James F. Hoburg, Brian T. Kirby, James Kuffner, Peter Lee, Todd C. Mowry, Padmanabhan Pillai, Ram Ravichandran, Benjamin D. Rister, Srinivasan Seshan, Metin Sitti, Haifeng Yu:
Claytronics: highly scalable communications, sensing, and actuation networks. SenSys 2005: 299
Informal and Other Publications
- 2024
- [i9]Xinzhu Liang, Sanjaya Lohani, Joseph M. Lukens, Brian T. Kirby, Thomas A. Searles, Kody J. H. Law:
SMC Is All You Need: Parallel Strong Scaling. CoRR abs/2402.06173 (2024) - 2023
- [i8]Zhihui Zhu, Joseph M. Lukens, Brian T. Kirby:
On the connection between least squares, regularization, and classical shadows. CoRR abs/2310.16921 (2023) - 2022
- [i7]Sanjaya Lohani, Joseph M. Lukens, Ryan T. Glasser, Thomas A. Searles, Brian T. Kirby:
Data-Centric Machine Learning in Quantum Information Science. CoRR abs/2201.09134 (2022) - [i6]Sanjaya Lohani, Sangita Regmi, Joseph M. Lukens, Ryan T. Glasser, Thomas A. Searles, Brian T. Kirby:
Dimension-adaptive machine-learning-based quantum state reconstruction. CoRR abs/2205.05804 (2022) - [i5]Manon P. Bart, Nicholas J. Savino, Paras Regmi, Lior Cohen, Haleh Safavi, Harry C. Shaw, Sanjaya Lohani, Thomas A. Searles, Brian T. Kirby, Hwang Lee, Ryan T. Glasser:
Deep learning for enhanced free-space optical communications. CoRR abs/2208.07712 (2022) - [i4]Sanjaya Lohani, Joseph M. Lukens, Atiyya A. Davis, Amirali Khannejad, Sangita Regmi, Daniel E. Jones, Ryan T. Glasser, Thomas A. Searles, Brian T. Kirby:
Demonstration of machine-learning-enhanced Bayesian quantum state estimation. CoRR abs/2212.08032 (2022) - 2021
- [i3]Sanjaya Lohani, Joseph M. Lukens, Daniel E. Jones, Thomas A. Searles, Ryan T. Glasser, Brian T. Kirby:
Improving application performance with biased distributions of quantum states. CoRR abs/2107.07642 (2021) - 2020
- [i2]Sanjaya Lohani, Brian T. Kirby, Michael Brodsky, Onur Danaci, Ryan T. Glasser:
Machine learning assisted quantum state estimation. CoRR abs/2003.03441 (2020) - [i1]Sanjaya Lohani, Thomas A. Searles, Brian T. Kirby, Ryan T. Glasser:
On the experimental feasibility of quantum state reconstruction via machine learning. CoRR abs/2012.09432 (2020)
Coauthor Index
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