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ORCIDCatherine D. Schuman
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- affiliation: University of Tennessee, Knoxville, TN, USA
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2020 – today
- 2024
[j19]Felix Wang
, Shruti R. Kulkarni, Bradley H. Theilman, Fredrick H. Rothganger, Catherine D. Schuman, Seung-Hwan Lim, James B. Aimone:
Scaling neural simulations in STACS. Neuromorph. Comput. Eng. 4(2): 24002 (2024)- [j18]Nishith N. Chakraborty, Shelah Ameli, Hritom Das, Catherine D. Schuman, Garrett S. Rose:
Hardware software co-design for leveraging STDP in a memristive neuroprocessor. Neuromorph. Comput. Eng. 4(2): 24010 (2024) - [c93]Shay Snyder, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa:
Transductive Spiking Graph Neural Networks for Loihi. ACM Great Lakes Symposium on VLSI 2024: 608-613 - [c92]Suma George Cardwell, Karan Patel, Catherine D. Schuman, J. Darby Smith, Jaesuk Kwon, Andrew Maicke, Jared Arzate, Jean Anne C. Incorvia:
Device Codesign using Reinforcement Learning. ISCAS 2024: 1-5 - [c91]Catherine D. Schuman, Hritom Das, Garrett S. Rose, James S. Plank:
Evaluation of Neuron Parameters on the Performance of Spiking Neural Networks and Neuromorphic Hardware. ISVLSI 2024: 337-342 - [c90]Hritom Das, Nishith N. Chakraborty, Manu Rathore, Sk Hasibul Alam, Catherine D. Schuman, Garrett S. Rose:
A Memristive Reconfigurable Neuromorphic Array for Neuro-Inspired Dynamic Architectures. ISVLSI 2024: 415-420 - [c89]Hritom Das, Karan P. Patel, Shelah Ameli, Nishith N. Chakraborty, Catherine D. Schuman, Garrett S. Rose:
Hardware-Application Co-Design to Evaluate the Performance of an STDP-based Reservoir Computer. ISVLSI 2024: 666-670 - [c88]Shruti R. Kulkarni, Anika Tabassum, Seung-Hwan Lim, Catherine D. Schuman, Bradley H. Theilman, Fred Rothganger, Felix Wang, James B. Aimone:
Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning. NICE 2024: 1-7 - [c87]Ashwani Kumar, Jaeseoung Park, Yucheng Zhou, Jeong-Hoon Kim, Soumil Jain, Catherine D. Schuman, Gert Cauwenberghs, Duygu Kuzum:
Energy Efficient Implementation of MVM Operations Using Filament-Free Bulk RRAM Array. NICE 2024: 1-5 - [c86]Catherine D. Schuman, Charles P. Rizzo, Garrett S. Rose, James S. Plank:
Embracing the Hairball: An Investigation of Recurrence in Spiking Neural Networks for Control. NICE 2024: 1-5 - [i27]Charles P. Rizzo, Catherine D. Schuman, James S. Plank:
Speed-based Filtration and DBSCAN of Event-based Camera Data with Neuromorphic Computing. CoRR abs/2401.15212 (2024) - [i26]Shay Snyder, Victoria Clerico, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Sumedh R. Risbud, Maryam Parsa:
Transductive Spiking Graph Neural Networks for Loihi. CoRR abs/2404.17048 (2024) - [i25]Derek Gobin, Shay Snyder, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Maryam Parsa:
Exploration of Novel Neuromorphic Methodologies for Materials Applications. CoRR abs/2405.04478 (2024) - 2023
- [j17]Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Chathika Gunaratne, Kenneth A. De Jong:
Avoiding excess computation in asynchronous evolutionary algorithms. Expert Syst. J. Knowl. Eng. 40(5) (2023) - [c85]Catherine D. Schuman, Hritom Das, James S. Plank, Ahmedullah Aziz, Garrett S. Rose:
Evaluating Neuron Models through Application-Hardware Co-Design. ACSSC 2023: 537-542 - [c84]Seoyoung An, Georgia Channing, Catherine D. Schuman, Michela Taufer:
VINARCH: A Visual Analytics Interactive Tool for Neural Network Archaeology. CLUSTER Workshops 2023: 50-51 - [c83]Guojing Cong, Shruti R. Kulkarni, Seung-Hwan Lim, Prasanna Date, Shay Snyder, Maryam Parsa, Dominic Kennedy, Catherine D. Schuman:
Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation. ICMLA 2023: 1541-1546 - [c82]Shruti R. Kulkarni, Aaron R. Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey S. Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine D. Schuman, Alice Bean:
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments. ICONS 2023: 3:1-3:8 - [c81]Charles Rizzo, Luke Mccombs, Braxton Haynie, Catherine D. Schuman, James S. Plank:
DVSGesture Recognition with Neuromorphic Observation Space Reduction Techniques. ICONS 2023: 10:1-10:8 - [c80]James Ghawaly, Aaron R. Young, Andrew D. Nicholson, Brett Witherspoon, Nick Prins, Mathew Swinney, Cihangir Celik, Catherine D. Schuman, Karan Patel:
Performance Optimization Study of the Neuromorphic Radiation Anomaly Detector. ICONS 2023: 13:1-13:7 - [c79]Lillian Sharpe, Julia Steed, Md. Mazharul Islam, Ahmedullah Aziz, Catherine D. Schuman:
Impact of Neuron Firing Rate on Application and Algorithm Performance. ICONS 2023: 14:1-14:4 - [c78]Shelah Ameli, Adam Z. Foshie, Drew Friend, James S. Plank, Garrett S. Rose, Catherine D. Schuman:
Algorithm and Application Impacts of Programmable Plasticity in Spiking Neuromorphic Hardware. ICONS 2023: 39:1-39:6 - [c77]Georgia Channing, Ria Patel, Paula Olaya, Ariel Keller Rorabaugh, Osamu Miyashita, Silvina Caíno-Lores, Catherine D. Schuman, Florence Tama, Michela Taufer:
Composable Workflow for Accelerating Neural Architecture Search Using In Situ Analytics for Protein Classification. ICPP 2023: 1 - [c76]Charles Rizzo, Catherine D. Schuman, James S. Plank:
Neuromorphic Downsampling of Event-Based Camera Output. NICE 2023: 26-34 - [c75]Karan P. Patel, Catherine D. Schuman:
Impact of Noisy Input on Evolved Spiking Neural Networks for Neuromorphic Systems. NICE 2023: 52-56 - [e6]Andrea Bartolini, Kristian F. D. Rietveld, Catherine D. Schuman, Jose Moreira:
Proceedings of the 20th ACM International Conference on Computing Frontiers, CF 2023, Bologna, Italy, May 9-11, 2023. ACM 2023 [contents] - [e5]Catherine D. Schuman, Melika Payvand, Maryam Parsa:
Proceedings of the 2023 International Conference on Neuromorphic Systems, ICONS 2023, Santa Fe, NM, USA, August 1-3, 2023. ACM 2023 [contents] - [i24]Jason Yik, Soikat Hasan Ahmed, Zergham Ahmed, Brian Anderson, Andreas G. Andreou, Chiara Bartolozzi, Arindam Basu, Douwe den Blanken, Petrut Bogdan, Sander M. Bohté, Younes Bouhadjar, Sonia M. Buckley, Gert Cauwenberghs, Federico Corradi, Guido de Croon, Andreea Danielescu, Anurag Reddy Daram, Mike Davies, Yigit Demirag, Jason Eshraghian, Jeremy Forest, Steve B. Furber, Michael Furlong, Aditya Gilra, Giacomo Indiveri, Siddharth Joshi, Vedant Karia, Lyes Khacef, James C. Knight, Laura Kriener, Rajkumar Kubendran, Dhireesha Kudithipudi, Gregor Lenz, Rajit Manohar, Christian Mayr, Konstantinos P. Michmizos, Dylan R. Muir, Emre Neftci, Thomas Nowotny, Fabrizio Ottati, Ayça Özcelikkale, Noah Pacik-Nelson, Priyadarshini Panda, Pao-Sheng Sun, Melika Payvand, Christian Pehle, Mihai A. Petrovici, Christoph Posch, Alpha Renner, Yulia Sandamirskaya, Clemens JS Schaefer, André van Schaik, Johannes Schemmel, Catherine D. Schuman, Jae-sun Seo, Sumit Bam Shrestha, Manolis Sifalakis, Amos Sironi, Kenneth Michael Stewart, Terrence C. Stewart, Philipp Stratmann, Guangzhi Tang, Jonathan Timcheck, Marian Verhelst, Craig M. Vineyard, Bernhard Vogginger, Amirreza Yousefzadeh, Biyan Zhou, Fatima Tuz Zohora, Charlotte Frenkel, Vijay Janapa Reddi:
NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. CoRR abs/2304.04640 (2023) - [i23]Céline van Valkenhoef, Catherine D. Schuman, Philip Walther:
Benchmarking the human brain against computational architectures. CoRR abs/2305.14363 (2023) - [i22]Hritom Das, Nishith N. Chakraborty, Catherine D. Schuman, Garrett S. Rose:
Enhanced Read Resolution in Reconfigurable Memristive Synapses for Spiking Neural Networks. CoRR abs/2306.13721 (2023) - [i21]Shruti R. Kulkarni, Aaron R. Young, Prasanna Date, Narasinga Rao Miniskar, Jeffrey S. Vetter, Farah Fahim, Benjamin Parpillon, Jennet Dickinson, Nhan Tran, Jieun Yoo, Corrinne Mills, Morris Swartz, Petar Maksimovic, Catherine D. Schuman, Alice Bean:
On-Sensor Data Filtering using Neuromorphic Computing for High Energy Physics Experiments. CoRR abs/2307.11242 (2023) - [i20]Adam Z. Foshie, James S. Plank, Garrett S. Rose, Catherine D. Schuman:
Functional Specification of the RAVENS Neuroprocessor. CoRR abs/2307.15232 (2023) - [i19]Md. Mazharul Islam, Shamiul Alam, Catherine D. Schuman, Md. Shafayat Hossain, Ahmedullah Aziz:
A Deep Dive into the Design Space of a Dynamically Reconfigurable Cryogenic Spiking Neuron. CoRR abs/2308.15754 (2023) - [i18]Md Sakib Hasan, Catherine D. Schuman, Zhongyang Zhang, Tauhidur Rahman, Garrett S. Rose:
Spike-based Neuromorphic Computing for Next-Generation Computer Vision. CoRR abs/2310.09692 (2023) - [i17]Jaeseoung Park, Ashwani Kumar, Yucheng Zhou, Sangheon Oh, Jeong-Hoon Kim, Yuhan Shi, Soumil Jain, Gopabandhu Hota, Amelie L. Nagle, Catherine D. Schuman, Gert Cauwenberghs, Duygu Kuzum:
Multi-level, Forming Free, Bulk Switching Trilayer RRAM for Neuromorphic Computing at the Edge. CoRR abs/2310.13844 (2023) - 2022
- [j16]Bon Woong Ku, Catherine D. Schuman, Md Musabbir Adnan, Tiffany M. Mintz, Raphael C. Pooser, Kathleen E. Hamilton, Garrett S. Rose, Sung Kyu Lim:
Unsupervised Digit Recognition Using Cosine Similarity In A Neuromemristive Competitive Learning System. ACM J. Emerg. Technol. Comput. Syst. 18(2): 38:1-38:20 (2022) - [j15]Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Prasanna Date, Bill Kay:
Opportunities for neuromorphic computing algorithms and applications. Nat. Comput. Sci. 2(1): 10-19 (2022) - [j14]Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Prasanna Date, Bill Kay:
Publisher Correction: Opportunities for neuromorphic computing algorithms and applications. Nat. Comput. Sci. 2(3): 205 (2022) - [j13]Catherine D. Schuman, Robert M. Patton, Shruti R. Kulkarni, Maryam Parsa, Christopher G. Stahl, Nicholas Quentin Haas, J. Parker Mitchell, Shay Snyder, Amelie Nagle, Alexandra Shanafield, Thomas E. Potok:
Evolutionary vs imitation learning for neuromorphic control at the edge. Neuromorph. Comput. Eng. 2(1): 14002 (2022) - [j12]James B. Aimone, Prasanna Date, Gabriel A. Fonseca Guerra, Kathleen E. Hamilton, Kyle Henke, Bill Kay, Garrett T. Kenyon, Shruti R. Kulkarni, Susan M. Mniszewski, Maryam Parsa, Sumedh R. Risbud, Catherine D. Schuman, William Severa, J. Darby Smith:
A review of non-cognitive applications for neuromorphic computing. Neuromorph. Comput. Eng. 2(2): 32003 (2022) - [j11]Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell:
Next-Cycle Optimal Dilute Combustion Control via Online Learning of Cycle-to-Cycle Variability Using Kernel Density Estimators. IEEE Trans. Control. Syst. Technol. 30(6): 2433-2449 (2022) - [j10]Scott Pakin, Christof Teuscher, Catherine D. Schuman:
Guest Editorial: Special Section on Parallel and Distributed Computing Techniques for Non-Von Neumann Technologies. IEEE Trans. Parallel Distributed Syst. 33(2): 249-250 (2022) - [c74]Ria Patel, Ariel Keller Rorabaugh, Paula Olaya, Silvina Caíno-Lores, Georgia Channing, Catherine D. Schuman, Osamu Miyashita, Florence Tama, Michela Taufer:
A Methodology to Generate Efficient Neural Networks for Classification of Scientific Datasets. e-Science 2022: 389-390 - [c73]Catherine D. Schuman, Charles Rizzo, John McDonald-Carmack, Nicholas D. Skuda, James S. Plank:
Evaluating Encoding and Decoding Approaches for Spiking Neuromorphic Systems. ICONS 2022: 2:1-2:9 - [c72]Prasanna Date, Thomas E. Potok, Catherine D. Schuman, Bill Kay:
Neuromorphic Computing is Turing-Complete. ICONS 2022: 16:1-16:10 - [c71]James Ghawaly, Aaron R. Young, Dan Archer, Nick Prins, Brett Witherspoon, Catherine D. Schuman:
A Neuromorphic Algorithm for Radiation Anomaly Detection. ICONS 2022: 22:1-22:6 - [c70]Charles Rizzo, Catherine D. Schuman, James S. Plank:
Event-Based Camera Simulation Wrapper for Arcade Learning Environment. ICONS 2022: 24:1-24:5 - [c69]Guojing Cong, Seung-Hwan Lim, Shruti R. Kulkarni, Prasanna Date, Thomas E. Potok, Shay Snyder, Maryam Parsa, Catherine D. Schuman:
Semi-Supervised Graph Structure Learning on Neuromorphic Computers. ICONS 2022: 28:1-28:4 - [c68]Mark Coletti, Chathika Gunaratne, Catherine D. Schuman, Robert M. Patton:
Training reinforcement learning models via an adversarial evolutionary algorithm. ICPP Workshops 2022: 23:1-23:6 - [c67]Suma George Cardwell, Catherine D. Schuman, J. Darby Smith, Karan Patel, Jaesuk Kwon, Samuel Liu, Christopher Allemang, Shashank Misra, Jean Anne C. Incorvia, James B. Aimone:
Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation. ICRC 2022: 57-65 - [c66]Prasanna Date, Shruti R. Kulkarni, Aaron R. Young, Catherine D. Schuman, Thomas E. Potok, Jeffrey S. Vetter:
Virtual Neuron: A Neuromorphic Approach for Encoding Numbers. ICRC 2022: 100-105 - [c65]Catherine D. Schuman, James S. Plank, Robert M. Patton, Thomas E. Potok, Garrett S. Rose:
A Framework to Enable Top-Down Co-Design of Neuromorphic Systems for Real-World Applications. NICE 2022: 84-85 - [c64]Robert M. Patton, Prasanna Date, Shruti R. Kulkarni, Chathika Gunaratne, Seung-Hwan Lim, Guojing Cong, Steven R. Young, Mark Coletti, Thomas E. Potok, Catherine D. Schuman:
Neuromorphic Computing for Scientific Applications. RSDHA@SC 2022: 22-28 - [e4]Thomas E. Potok, Catherine D. Schuman, Melika Payvand, Prasanna Date, Shruti R. Kulkarni, Yiran Chen, Robinson E. Pino, Brad Aimone, Mutsumi Kimura, Gregory Cohen, David Whittaker, Gordon Hirsch Wilson:
ICONS 2022: International Conference on Neuromorphic Systems, Knoxville, TN, USA, July 27 - 29, 2022. ACM 2022, ISBN 978-1-4503-9789-6 [contents] - [i16]James S. Plank, Chaohui Zheng, Bryson Gullett, Nicholas D. Skuda, Charles Rizzo, Catherine D. Schuman, Garrett S. Rose:
The Case for RISP: A Reduced Instruction Spiking Processor. CoRR abs/2206.14016 (2022) - [i15]Prasanna Date, Shruti R. Kulkarni, Aaron R. Young, Catherine D. Schuman, Thomas E. Potok, Jeffrey S. Vetter:
Encoding Integers and Rationals on Neuromorphic Computers using Virtual Neuron. CoRR abs/2208.07468 (2022) - [i14]Samuel Schmidgall, Catherine D. Schuman, Maryam Parsa:
Biological connectomes as a representation for the architecture of artificial neural networks. CoRR abs/2209.14406 (2022) - [i13]James S. Plank, Bryson Gullett, Adam Z. Foshie, Garrett S. Rose, Catherine D. Schuman:
Disclosure of a Neuromorphic Starter Kit. CoRR abs/2211.04526 (2022) - [i12]Suma George Cardwell, Catherine D. Schuman, J. Darby Smith, Karan Patel, Jaesuk Kwon, Samuel Liu, Christopher Allemang, Shashank Misra, Jean Anne C. Incorvia, James B. Aimone:
Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation. CoRR abs/2212.00625 (2022) - 2021
- [j9]Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell:
Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion. IEEE Control. Syst. Lett. 5(6): 2204-2209 (2021) - [j8]Wilkie Olin-Ammentorp, Karsten Beckmann, Catherine D. Schuman, James S. Plank, Nathaniel C. Cady:
Stochasticity and robustness in spiking neural networks. Neurocomputing 419: 23-36 (2021) - [j7]Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman:
Benchmarking the performance of neuromorphic and spiking neural network simulators. Neurocomputing 447: 145-160 (2021) - [j6]Md Musabbir Adnan, Sagarvarma Sayyaparaju, Samuel D. Brown, Mst Shamim Ara Shawkat, Catherine D. Schuman, Garrett S. Rose:
Design of a Robust Memristive Spiking Neuromorphic System with Unsupervised Learning in Hardware. ACM J. Emerg. Technol. Comput. Syst. 17(4): 56:1-56:26 (2021) - [c63]Bryan P. Maldonado, Brian C. Kaul, Catherine D. Schuman, Steven R. Young, J. Parker Mitchell:
Next-Cycle Optimal Fuel Control for Cycle-to-Cycle Variability Reduction in EGR-Diluted Combustion. ACC 2021: 1830-1835 - [c62]Maryam Parsa, Shruti R. Kulkarni, Mark Coletti, Jeffrey K. Bassett, J. Parker Mitchell, Catherine D. Schuman:
Multi-Objective Hyperparameter Optimization for Spiking Neural Network Neuroevolution. CEC 2021: 1225-1232 - [c61]Catherine D. Schuman, Steven R. Young, Bryan P. Maldonado, Brian C. Kaul:
Real-Time Evolution and Deployment of Neuromorphic Computing at The Edge. IGSC (Workshops) 2021: 1-8 - [c60]J. Parker Mitchell, Catherine D. Schuman:
Low Power Hardware-In-The-Loop Neuromorphic Training Accelerator. ICONS 2021: 4:1-4:4 - [c59]Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman:
Training Spiking Neural Networks with Synaptic Plasticity under Integer Representation. ICONS 2021: 6:1-6:7 - [c58]Prasanna Date, Bill Kay, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok:
Computational Complexity of Neuromorphic Algorithms. ICONS 2021: 8:1-8:7 - [c57]Maryam Parsa, Catherine D. Schuman, Nitin Rathi, Amirkoushyar Ziabari, Derek C. Rose, J. Parker Mitchell, J. Travis Johnston, Bill Kay, Steven R. Young, Kaushik Roy:
Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. ICONS 2021: 14:1-14:8 - [c56]James S. Plank, Chaohui Zheng, Catherine D. Schuman, Christopher Dean:
Spiking Neuromorphic Networks for Binary Tasks. ICONS 2021: 22:1-22:9 - [c55]Robert M. Patton, Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Nicholas Quentin Haas, Christopher G. Stahl, Spencer Paulissen, Prasanna Date, Thomas E. Potok, Shay Sneider:
Neuromorphic Computing for Autonomous Racing. ICONS 2021: 23:1-23:5 - [c54]Bill Kay, Catherine D. Schuman, Jade O'Connor, Prasanna Date, Thomas E. Potok:
Neuromorphic Graph Algorithms: Cycle Detection, Odd Cycle Detection, and Max Flow. ICONS 2021: 24:1-24:7 - [c53]Catherine D. Schuman, James S. Plank, Maryam Parsa, Shruti R. Kulkarni, Nicholas D. Skuda, J. Parker Mitchell:
A Software Framework for Comparing Training Approaches for Spiking Neuromorphic Systems. IJCNN 2021: 1-10 - [c52]Catherine D. Schuman, Bill Kay, Prasanna Date, Ramakrishnan Kannan, Piyush Sao, Thomas E. Potok:
Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers. IPDPS Workshops 2021: 308-311 - [c51]Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Kenneth A. De Jong:
Avoiding Excess Computation in Asynchronous Evolutionary Algorithms. UKCI 2021: 71-82 - [e3]Thomas E. Potok, Melika Payvand, Catherine D. Schuman, Prasanna Date, Mutsumi Kimura, Cory E. Merkel, Brad Aimone, Sonia M. Buckley, Yiran Chen, Gregory Cohen, Todd Hylton, Robert M. Patton, Robinson E. Pino, Garrett S. Rose:
ICONS 2021: International Conference on Neuromorphic Systems 2021, Knoxville, TN, USA, July 27-29, 2021. ACM 2021, ISBN 978-1-4503-8691-3 [contents] - [i11]Prasanna Date, Catherine D. Schuman, Bill Kay, Thomas E. Potok:
Neuromorphic Computing is Turing-Complete. CoRR abs/2104.13983 (2021) - [i10]James S. Plank, Catherine D. Schuman, Robert M. Patton:
An Oracle and Observations for the OpenAI Gym / ALE Freeway Environment. CoRR abs/2109.01220 (2021) - 2020
- [j5]Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Ryan S. Bennink, Neena Imam, Travis S. Humble:
Accelerating Scientific Computing in the Post-Moore's Era. ACM Trans. Parallel Comput. 7(1): 6:1-6:31 (2020) - [c50]Catherine D. Schuman, Steven R. Young, J. Parker Mitchell, J. Travis Johnston, Derek C. Rose, Bryan P. Maldonado, Brian C. Kaul:
Low Size, Weight, and Power Neuromorphic Computing to Improve Combustion Engine Efficiency. IGSC (Workshops) 2020: 1-8 - [c49]Daniel Elbrecht, Catherine D. Schuman:
Neuroevolution of Spiking Neural Networks Using Compositional Pattern Producing Networks. ICONS 2020: 4:1-4:5 - [c48]J. Parker Mitchell, Catherine D. Schuman, Thomas E. Potok:
A Small, Low Cost Event-Driven Architecture for Spiking Neural Networks on FPGAs. ICONS 2020: 16:1-16:4 - [c47]Kathleen E. Hamilton, Tiffany M. Mintz, Prasanna Date, Catherine D. Schuman:
Spike-based graph centrality measures. ICONS 2020: 26:1-26:8 - [c46]Kathleen E. Hamilton, Prasanna Date, Bill Kay, Catherine D. Schuman:
Modeling epidemic spread with spike-based models. ICONS 2020: 28:1-28:5 - [c45]Jonathan D. Ambrose, Adam Z. Foshie, Mark E. Dean, James S. Plank, Garrett S. Rose, J. Parker Mitchell, Catherine D. Schuman, Grant Bruer:
GRANT: Ground-Roaming Autonomous Neuromorphic Targeter. IJCNN 2020: 1-8 - [c44]Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. IJCNN 2020: 1-9 - [c43]Catherine D. Schuman, J. Parker Mitchell, J. Travis Johnston, Maryam Parsa, Bill Kay, Prasanna Date, Robert M. Patton:
Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems. IJCNN 2020: 1-10 - [c42]Catherine D. Schuman, J. Parker Mitchell, Maryam Parsa, James S. Plank, Samuel D. Brown, Garrett S. Rose, Robert M. Patton, Thomas E. Potok:
Automated Design of Neuromorphic Networks for Scientific Applications at the Edge. IJCNN 2020: 1-7 - [c41]Aaron R. Young, Adam Z. Foshie, Mark E. Dean, James S. Plank, Garrett S. Rose, J. Parker Mitchell, Catherine D. Schuman:
Scaled-up Neuromorphic Array Communications Controller (SNACC) for Large-scale Neural Networks. IJCNN 2020: 1-8 - [c40]Catherine D. Schuman, J. Parker Mitchell, Robert M. Patton, Thomas E. Potok, James S. Plank:
Evolutionary Optimization for Neuromorphic Systems. NICE 2020: 2:1-2:9 - [c39]Bill Kay, Prasanna Date, Catherine D. Schuman:
Neuromorphic Graph Algorithms: Extracting Longest Shortest Paths and Minimum Spanning Trees. NICE 2020: 6:1-6:6 - [c38]J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok:
Caspian: A Neuromorphic Development Platform. NICE 2020: 8:1-8:6 - [c37]Daniel Elbrecht, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman:
Evolving Ensembles of Spiking Neural Networks for Neuromorphic Systems. SSCI 2020: 1989-1994 - [c36]Daniel Elbrecht, Maryam Parsa, Shruti R. Kulkarni, J. Parker Mitchell, Catherine D. Schuman:
Training Spiking Neural Networks Using Combined Learning Approaches. SSCI 2020: 1995-2001 - [e2]Thomas E. Potok, Catherine D. Schuman:
Proceedings of the International Conference on Neuromorphic Systems, ICONS 2020, Oak Ridge, Tennessee, USA, July, 2020. ACM 2020, ISBN 978-1-4503-8851-1 [contents] - [i9]Mihaela Dimovska, Travis Johnston, Catherine D. Schuman, J. Parker Mitchell, Thomas E. Potok:
Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks. CoRR abs/2002.01406 (2020) - [i8]Theodore Papamarkou, Hayley Guy, Bryce Kroencke, Jordan Miller, Preston Robinette, Daniel Schultz, Jacob D. Hinkle, Laura Pullum, Catherine D. Schuman, Jeremy Renshaw, Stylianos Chatzidakis:
Automated detection of pitting and stress corrosion cracks in used nuclear fuel dry storage canisters using residual neural networks. CoRR abs/2003.03241 (2020) - [i7]Maryam Parsa, Catherine D. Schuman, Prasanna Date, Derek C. Rose, Bill Kay, J. Parker Mitchell, Steven R. Young, Ryan Dellana, William Severa, Thomas E. Potok, Kaushik Roy:
Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment. CoRR abs/2005.04171 (2020)
2010 – 2019
- 2019
- [j4]Prasanna Date, Robert M. Patton, Catherine D. Schuman, Thomas E. Potok:
Efficiently embedding QUBO problems on adiabatic quantum computers. Quantum Inf. Process. 18(4): 117 (2019) - [c35]Robert M. Patton, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou:
Exascale Deep Learning to Accelerate Cancer Research. IEEE BigData 2019: 1488-1496 - [c34]Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok, Kaushik Roy:
Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems. IEEE BigData 2019: 4472-4478 - [c33]Steven R. Young, Pravallika Devineni, Maryam Parsa, J. Travis Johnston, Bill Kay, Robert M. Patton, Catherine D. Schuman, Derek C. Rose, Thomas E. Potok:
Evolving Energy Efficient Convolutional Neural Networks. IEEE BigData 2019: 4479-4485 - [c32]Junghoon Chae, Catherine D. Schuman, Steven R. Young, J. Travis Johnston, Derek C. Rose, Robert M. Patton, Thomas E. Potok:
Visualization System for Evolutionary Neural Networks for Deep Learning. IEEE BigData 2019: 4498-4502 - [c31]Catherine D. Schuman, James S. Plank, Robert M. Patton, Thomas E. Potok:
Island model for parallel evolutionary optimization of spiking neuromorphic computing. GECCO (Companion) 2019: 306-307 - [c30]Linghao Song, Fan Chen, Steven R. Young, Catherine D. Schuman, Gabriel N. Perdue, Thomas E. Potok:
Deep Learning for Vertex Reconstruction of Neutrino-nucleus Interaction Events with Combined Energy and Time Data. ICASSP 2019: 3882-3886 - [c29]John J. M. Reynolds, James S. Plank, Catherine D. Schuman:
Intelligent Reservoir Generation for Liquid State Machines using Evolutionary Optimization. IJCNN 2019: 1-8 - [c28]Catherine D. Schuman, James S. Plank, Grant Bruer, Jeremy Anantharaj:
Non-Traditional Input Encoding Schemes for Spiking Neuromorphic Systems. IJCNN 2019: 1-10 - [c27]Jeremy T. Johnston, Steven R. Young, Catherine D. Schuman, Junghoon Chae, Don D. March, Robert M. Patton, Thomas E. Potok:
Fine-Grained Exploitation of Mixed Precision for Faster CNN Training. MLHPC@SC 2019: 9-18 - [c26]Mihaela Dimovska, Travis Johnston, Catherine D. Schuman, J. Parker Mitchell, Thomas E. Potok:
Multi-Objective Optimization for Size and Resilience of Spiking Neural Networks. UEMCON 2019: 433-439 - [e1]Thomas E. Potok, Catherine D. Schuman:
Proceedings of the International Conference on Neuromorphic Systems, ICONS 2019, Knoxville, Tennessee, USA, July 23-25, 2019. ACM 2019, ISBN 978-1-4503-7680-8 [contents] - [i6]Linghao Song, Fan Chen, Steven R. Young, Catherine D. Schuman, Gabriel N. Perdue, Thomas E. Potok:
Deep Learning for Vertex Reconstruction of Neutrino-Nucleus Interaction Events with Combined Energy and Time Data. CoRR abs/1902.00743 (2019) - [i5]Kathleen E. Hamilton, Tiffany M. Mintz, Catherine D. Schuman:
Spike-based primitives for graph algorithms. CoRR abs/1903.10574 (2019) - [i4]Wilkie Olin-Ammentorp, Karsten Beckmann, Catherine D. Schuman, James S. Plank, Nathaniel C. Cady:
Stochasticity and Robustness in Spiking Neural Networks. CoRR abs/1906.02796 (2019) - [i3]Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou, Shahira Abousamra, Dimitris Samaras, Joel H. Saltz:
Exascale Deep Learning to Accelerate Cancer Research. CoRR abs/1909.12291 (2019) - 2018
- [j3]Jeremy Liu, Federico M. Spedalieri, Ke-Thia Yao, Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Garrett S. Rose, Gangotree Chakma:
Adiabatic Quantum Computation Applied to Deep Learning Networks. Entropy 20(5): 380 (2018) - [j2]Gangotree Chakma, Md Musabbir Adnan, Austin Wyer, Ryan Weiss, Catherine D. Schuman, Garrett S. Rose:
Memristive Mixed-Signal Neuromorphic Systems: Energy-Efficient Learning at the Circuit-Level. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(1): 125-136 (2018) - [j1]Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Federico M. Spedalieri, Jeremy Liu, Ke-Thia Yao, Garrett S. Rose, Gangotree Chakma:
A Study of Complex Deep Learning Networks on High-Performance, Neuromorphic, and Quantum Computers. ACM J. Emerg. Technol. Comput. Syst. 14(2): 19:1-19:21 (2018) - [c25]Ryan Weiss, Joseph S. Najem, Md Sakib Hasan, Catherine D. Schuman, Alex Belianinov, C. Patrick Collier, Stephen A. Sarles, Garrett S. Rose:
A Soft-Matter Biomolecular Memristor Synapse for Neuromorphic Systems. BioCAS 2018: 1-4 - [c24]Gangotree Chakma, Nicholas D. Skuda, Catherine D. Schuman, James S. Plank, Mark E. Dean, Garrett S. Rose:
Energy and Area Efficiency in Neuromorphic Computing for Resource Constrained Devices. ACM Great Lakes Symposium on VLSI 2018: 379-383 - [c23]Sonia M. Buckley, Adam N. McCaughan, Jeff Chiles, Richard P. Mirin, Sae Woo Nam, Jeffrey M. Shainline, Grant Bruer, James S. Plank, Catherine D. Schuman:
Design of Superconducting Optoelectronic Networks for Neuromorphic Computing. ICRC 2018: 1-7 - [c22]Catherine D. Schuman, Grant Bruer, Aaron R. Young, Mark E. Dean, James S. Plank:
Understanding Selection And Diversity For Evolution Of Spiking Recurrent Neural Networks. IJCNN 2018: 1-8 - [c21]Aaron R. Young, Mark E. Dean, James S. Plank, Garrett S. Rose, Catherine D. Schuman:
Neuromorphic Array Communications Controller to Support Large-Scale Neural Networks. IJCNN 2018: 1-8 - [c20]Kathleen E. Hamilton, Catherine D. Schuman, Steven R. Young, Neena Imam, Travis S. Humble:
Neural Networks and Graph Algorithms with Next-Generation Processors. IPDPS Workshops 2018: 1194-1203 - [c19]Nicholas D. Skuda, Catherine D. Schuman, Gangotree Chakma, James S. Plank, Garrett S. Rose:
High-Level Simulation for Spiking Neuromorphic Computing Systems. ISCAS 2018: 1-5 - [c18]Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Don D. March, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Thomas P. Karnowski, Maxim A. Ziatdinov, Sergei V. Kalinin:
167-PFlops deep learning for electron microscopy: from learning physics to atomic manipulation. SC 2018: 50:1-50:11 - [c17]Md Musabbir Adnan, Sagarvarma Sayyaparaju, Garrett S. Rose, Catherine D. Schuman, Bon Woong Ku, Sung Kyu Lim:
A Twin Memristor Synapse for Spike Timing Dependent Learning in Neuromorphic Systems. SoCC 2018: 37-42 - 2017
- [c16]James S. Plank, Garrett S. Rose, Mark E. Dean, Catherine D. Schuman, Nathaniel C. Cady:
A Unified Hardware/Software Co-Design Framework for Neuromorphic Computing Devices and Applications. ICRC 2017: 1-8 - [c15]Catherine D. Schuman:
The effect of biologically-inspired mechanisms in spiking neural networks for neuromorphic implementation. IJCNN 2017: 2636-2643 - [c14]Aleksander Klibisz, Grant Bruer, James S. Plank, Catherine D. Schuman:
Structure-based fitness prediction for the variable-structure DANNA neuromorphic architecture. IJCNN 2017: 3431-3438 - [c13]Catherine D. Schuman, James S. Plank, Garrett S. Rose, Gangotree Chakma, Austin Wyer, Grant Bruer, Nouamane Laanait:
A programming framework for neuromorphic systems with emerging technologies. NANOCOM 2017: 15:1-15:7 - [c12]Catherine D. Schuman, Thomas E. Potok, Steven R. Young, Robert M. Patton, Gabriel N. Perdue, Gangotree Chakma, Austin Wyer, Garrett S. Rose:
Neuromorphic computing for temporal scientific data classification. NCS 2017: 2:1-2:6 - [c11]Austin Wyer, Md Musabbir Adnan, Bon Woong Ku, Sung Kyu Lim, Catherine D. Schuman, Raphael C. Pooser, Garrett S. Rose:
Evaluating online-learning in memristive neuromorphic circuits. NCS 2017: 5:1-5:8 - [i2]Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Federico M. Spedalieri, Jeremy Liu, Ke-Thia Yao, Garrett S. Rose, Gangotree Chakma:
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. CoRR abs/1703.05364 (2017) - [i1]Catherine D. Schuman, Thomas E. Potok, Robert M. Patton, J. Douglas Birdwell, Mark E. Dean, Garrett S. Rose, James S. Plank:
A Survey of Neuromorphic Computing and Neural Networks in Hardware. CoRR abs/1705.06963 (2017) - 2016
- [c10]Catherine D. Schuman, James S. Plank, Adam Disney, John Reynolds:
An evolutionary optimization framework for neural networks and neuromorphic architectures. IJCNN 2016: 145-154 - [c9]Mark E. Dean, Jason Chan, Christopher Daffron, Adam Disney, John Reynolds, Garrett S. Rose, James S. Plank, J. Douglas Birdwell, Catherine D. Schuman:
An Application Development Platform for neuromorphic computing. IJCNN 2016: 1347-1354 - [c8]Catherine D. Schuman, Adam Disney, Susheela P. Singh, Grant Bruer, J. Parker Mitchell, Aleksander Klibisz, James S. Plank:
Parallel Evolutionary Optimization for Neuromorphic Network Training. MLHPC@SC 2016: 36-46 - [c7]Thomas E. Potok, Catherine D. Schuman, Steven R. Young, Robert M. Patton, Federico M. Spedalieri, Jeremy Liu, Ke-Thia Yao, Garrett S. Rose, Gangotree Chakma:
A Study of Complex Deep Learning Networks on High Performance, Neuromorphic, and Quantum Computers. MLHPC@SC 2016: 47-55 - 2015
- [c6]Catherine D. Schuman, Adam Disney, John Reynolds:
Dynamic adaptive neural network arrays: a neuromorphic architecture. MLHPC@SC 2015: 3:1-3:4 - 2014
- [c5]Catherine D. Schuman, J. Douglas Birdwell, Mark E. Dean:
Spatiotemporal Classification Using Neuroscience-Inspired Dynamic Architectures. BICA 2014: 89-97 - [c4]Margaret Drouhard, Catherine D. Schuman, J. Douglas Birdwell, Mark E. Dean:
Visual analytics for neuroscience-inspired dynamic architectures. FOCI 2014: 106-113 - [c3]Mark E. Dean, Catherine D. Schuman, J. Douglas Birdwell:
Dynamic Adaptive Neural Network Array. UCNC 2014: 129-141 - 2012
- [c2]James S. Plank, Catherine D. Schuman, B. Devin Robison:
Heuristics for optimizing matrix-based erasure codes for fault-tolerant storage systems. DSN 2012: 1-12
2000 – 2009
- 2009
- [c1]James S. Plank, Jianqiang Luo, Catherine D. Schuman, Lihao Xu, Zooko Wilcox-O'Hearn:
A Performance Evaluation and Examination of Open-Source Erasure Coding Libraries for Storage. FAST 2009: 253-265
Coauthor Index
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