Maryam Parsa

According to our database, Maryam Parsa authored at least 33 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion Attacks.

Hamed Poursiami, Ihsen Alouani, Maryam Parsa

CoRR, 2024

2023

Avoiding excess computation in asynchronous evolutionary algorithms.

Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Chathika Gunaratne, Kenneth A. De Jong

Expert Syst. J. Knowl. Eng., June, 2023

Object Motion Sensitivity: A Bio-inspired Solution to the Ego-motion Problem for Event-based Cameras.

Shay Snyder, Hunter Thompson, Md. Abdullah-Al Kaiser, Gregory Schwartz, Akhilesh R. Jaiswal, Maryam Parsa

CoRR, 2023

Simulate Less, Expect More: Bringing Robot Swarms to Life via Low-Fidelity Simulations.

Ricardo Vega, Kevin Zhu, Sean Luke, Maryam Parsa, Cameron Nowzari

CoRR, 2023

Zespol: A Lightweight Environment for Training Swarming Agents.

Shay Snyder, Kevin Zhu, Ricardo Vega, Cameron Nowzari, Maryam Parsa

Proceedings of the 2023 International Conference on Neuromorphic Systems, 2023

Neuromorphic Bayesian Optimization in Lava.

Shay Snyder, Sumedh R. Risbud, Maryam Parsa

Proceedings of the 2023 International Conference on Neuromorphic Systems, 2023

Hyperparameter Optimization and Feature Inclusion in Graph Neural Networks for Spiking Implementation.

Guojing Cong, Shruti R. Kulkarni, Seung-Hwan Lim, Prasanna Date, Shay Snyder, Maryam Parsa, Dominic Kennedy, Catherine D. Schuman

Proceedings of the International Conference on Machine Learning and Applications, 2023

A Brain-inspired Approach for Malware Detection using Sub-semantic Hardware Features.

Maryam Parsa, Khaled N. Khasawneh, Ihsen Alouani

Proceedings of the Great Lakes Symposium on VLSI 2023, 2023

2022

A review of non-cognitive applications for neuromorphic computing.

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

Neuromorph. Comput. Eng., June, 2022

Evolutionary vs imitation learning for neuromorphic control at the edge.

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

Neuromorph. Comput. Eng., 2022

Publisher Correction: Opportunities for neuromorphic computing algorithms and applications.

Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Prasanna Date, Bill Kay

Nat. Comput. Sci., 2022

Opportunities for neuromorphic computing algorithms and applications.

Catherine D. Schuman, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Prasanna Date, Bill Kay

Nat. Comput. Sci., 2022

Biological connectomes as a representation for the architecture of artificial neural networks.

Samuel Schmidgall, Catherine D. Schuman, Maryam Parsa

CoRR, 2022

Semi-Supervised Graph Structure Learning on Neuromorphic Computers.

Guojing Cong, Seung-Hwan Lim, Shruti R. Kulkarni, Prasanna Date, Thomas E. Potok, Shay Snyder, Maryam Parsa, Catherine D. Schuman

Proceedings of the ICONS 2022: International Conference on Neuromorphic Systems, Knoxville, TN, USA, July 27, 2022

2021

Benchmarking the performance of neuromorphic and spiking neural network simulators.

Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman

Neurocomputing, 2021

Avoiding Excess Computation in Asynchronous Evolutionary Algorithms.

Eric O. Scott, Mark Coletti, Catherine D. Schuman, Bill Kay, Shruti R. Kulkarni, Maryam Parsa, Kenneth A. De Jong

Proceedings of the Advances in Computational Intelligence Systems, 2021

Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing.

Pravallika Devineni, Panchapakesan Ganesh, Nikhil Sivadas, Abhijeet Dhakane, Ketan Maheshwari, Drahomira Herrmannova, Ramakrishnan Kannan, Seung-Hwan Lim, Thomas E. Potok, Jordan B. Chipka, Priyantha Mudalige, Mark Coletti, Sajal Dash, Arnab Kumar Paul, Sarp Oral, Feiyi Wang, Bill Kay, Melissa R. Allen-Dumas, Christa Brelsford, Joshua R. New, Andy Berres, Kuldeep R. Kurte, Jibonananda Sanyal, Levi Sweet, Chathika Gunaratne, Maxim A. Ziatdinov, Rama K. Vasudevan, Sergei V. Kalinin, Olivera Kotevska, Jean C. Bilheux, Hassina Z. Bilheux, Garrett E. Granroth, Thomas Proffen, Rick Riedel, Peter F. Peterson, Shruti R. Kulkarni, Kyle P. Kelley, Stephen Jesse, Maryam Parsa

Proceedings of the Driving Scientific and Engineering Discoveries Through the Integration of Experiment, Big Data, and Modeling and Simulation, 2021

A Software Framework for Comparing Training Approaches for Spiking Neuromorphic Systems.

Catherine D. Schuman, James S. Plank, Maryam Parsa, Shruti R. Kulkarni, Nicholas D. Skuda, J. Parker Mitchell

Proceedings of the International Joint Conference on Neural Networks, 2021

Neuromorphic Computing for Autonomous Racing.

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

Proceedings of the ICONS 2021: International Conference on Neuromorphic Systems 2021, 2021

Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach.

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

Proceedings of the ICONS 2021: International Conference on Neuromorphic Systems 2021, 2021

Training Spiking Neural Networks with Synaptic Plasticity under Integer Representation.

Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman

Proceedings of the ICONS 2021: International Conference on Neuromorphic Systems 2021, 2021

Multi-Objective Hyperparameter Optimization for Spiking Neural Network Neuroevolution.

Maryam Parsa, Shruti R. Kulkarni, Mark Coletti, Jeffrey K. Bassett, J. Parker Mitchell, Catherine D. Schuman

Proceedings of the IEEE Congress on Evolutionary Computation, 2021

2020

Training Spiking Neural Networks Using Combined Learning Approaches.

Daniel Elbrecht, Maryam Parsa, Shruti R. Kulkarni, J. Parker Mitchell, Catherine D. Schuman

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Evolving Ensembles of Spiking Neural Networks for Neuromorphic Systems.

Daniel Elbrecht, Shruti R. Kulkarni, Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman

Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Automated Design of Neuromorphic Networks for Scientific Applications at the Edge.

Catherine D. Schuman, J. Parker Mitchell, Maryam Parsa, James S. Plank, Samuel D. Brown, Garrett S. Rose, Robert M. Patton, Thomas E. Potok

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Resilience and Robustness of Spiking Neural Networks for Neuromorphic Systems.

Catherine D. Schuman, J. Parker Mitchell, J. Travis Johnston, Maryam Parsa, Bill Kay, Prasanna Date, Robert M. Patton

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment.

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

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

2019

PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design.

Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy

Proceedings of the International Conference on Computer-Aided Design, 2019

Evolving Energy Efficient Convolutional Neural Networks.

Steven R. Young, Pravallika Devineni, Maryam Parsa, J. Travis Johnston, Bill Kay, Robert M. Patton, Catherine D. Schuman, Derek C. Rose, Thomas E. Potok

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

Bayesian-based Hyperparameter Optimization for Spiking Neuromorphic Systems.

Maryam Parsa, J. Parker Mitchell, Catherine D. Schuman, Robert M. Patton, Thomas E. Potok, Kaushik Roy

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2017

Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis.

Maryam Parsa, Priyadarshini Panda, Shreyas Sen, Kaushik Roy

Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

2016

Probabilistic Deep Spiking Neural Systems Enabled by Magnetic Tunnel Junction.

Abhronil Sengupta, Maryam Parsa, Bing Han, Kaushik Roy

CoRR, 2016

2012

Design and fabrication of a smart electronic guide for museums.

Majed Rostamian, Maryam Parsa, Voicu Groza

Proceedings of the 7th IEEE International Symposium on Applied Computational Intelligence and Informatics, 2012