Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDMaryam Parsa
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2023
[j3]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)- [i7]Ricardo Vega, Kevin Zhu, Sean Luke, Maryam Parsa, Cameron Nowzari:
Simulate Less, Expect More: Bringing Robot Swarms to Life via Low-Fidelity Simulations. CoRR abs/2301.09018 (2023) - [i6]Shay Snyder, Hunter Thompson, Md. Abdullah-Al Kaiser, Gregory Schwartz, Akhilesh R. Jaiswal, Maryam Parsa:
Object Motion Sensitivity: A Bio-inspired Solution to the Ego-motion Problem for Event-based Cameras. CoRR abs/2303.14114 (2023) - [i5]Shay Snyder, Sumedh R. Risbud, Maryam Parsa:
Neuromorphic Bayesian Optimization in Lava. CoRR abs/2305.11060 (2023) - 2022
- [j2]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) - [c18]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 - [i4]Samuel Schmidgall, Catherine D. Schuman, Maryam Parsa:
Biological connectomes as a representation for the architecture of artificial neural networks. CoRR abs/2209.14406 (2022) - 2021
- [j1]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) - [c17]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 - [c16]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 - [c15]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 - [c14]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 - [c13]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 - [c12]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:
Smoky Mountain Data Challenge 2021: An Open Call to Solve Scientific Data Challenges Using Advanced Data Analytics and Edge Computing. SMC 2021: 361-382 - [c11]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 - 2020
- [c10]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 - [c9]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 - [c8]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 - [c7]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 - [c6]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 - [i3]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
- [c5]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 - [c4]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 - [c3]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. ICCAD 2019: 1-8 - [i2]Maryam Parsa, Aayush Ankit, Amirkoushyar Ziabari, Kaushik Roy:
PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. CoRR abs/1906.08167 (2019) - 2017
- [c2]Maryam Parsa, Priyadarshini Panda, Shreyas Sen, Kaushik Roy:
Staged Inference using Conditional Deep Learning for energy efficient real-time smart diagnosis. EMBC 2017: 78-81 - 2016
- [i1]Abhronil Sengupta, Maryam Parsa, Bing Han, Kaushik Roy:
Probabilistic Deep Spiking Neural Systems Enabled by Magnetic Tunnel Junction. CoRR abs/1605.04494 (2016) - 2012
- [c1]Majed Rostamian, Maryam Parsa, Voicu Groza:
Design and fabrication of a smart electronic guide for museums. SACI 2012: 439-444
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
load content from web.archive.org
Privacy notice: By enabling the option above, your browser will contact the API of web.archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2023-05-28 01:16 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
