James B. Aimone

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 69

Top Topics

Scientific Computing

Top Venues

Publications

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)
Bradley H. Theilman, Qian Zhang, Adar Kahana, Eric C. Cyr, Nathaniel Trask, James B. Aimone, George Em Karniadakis
Spiking Physics-Informed Neural Networks on Loihi 2. NICE (2024)
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) (2024)
Bradley H. Theilman, Felix Wang, Fred Rothganger, James B. Aimone
Decomposing spiking neural networks with Graphical Neural Activity Threads. CoRR (2023)
James B. Aimone, Omar Awile, Markus Diesmann, James C. Knight, Thomas Nowotny, Felix Schürmann
Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute. Frontiers Neuroinformatics 17 (2023)
Peter Helfer, Corinne Teeter, Aaron J. Hill, Craig M. Vineyard, James B. Aimone, Dhireesha Kudithipudi
Context Modulation Enables Multi-tasking and Resource Efficiency in Liquid State Machines. ICONS (2023)
Bradley H. Theilman, James B. Aimone
Goemans-Williamson MAXCUT approximation algorithm on Loihi. NICE (2023)
James B. Aimone, William Severa, J. Darby Smith
Synaptic Sampling of Neural Networks. CoRR (2023)
Craig M. Vineyard, William M. Severa, James B. Aimone
Neuromorphic Co-Design as a Game. CoRR (2023)
David H. Wolpert, Jan Korbel, Christopher Lynn, Farita Tasnim, Joshua A. Grochow, Gülce Kardes, James B. Aimone, Vijay Balasubramanian, Eric De Giuli, David Doty, Nahuel Freitas, Matteo Marsili, Thomas E. Ouldridge, Andréa W. Richa, Paul M. Riechers, Édgar Roldán, Brenda M. Rubenstein, Zoltán Toroczkai, Joseph A. Paradiso
Is stochastic thermodynamics the key to understanding the energy costs of computation? CoRR (2023)
Dhireesha Kudithipudi, Anurag Reddy Daram, Abdullah M. Zyarah, Fatima Tuz Zohora, James B. Aimone, Angel Yanguas-Gil, Nicholas Soures, Emre Neftci, Matthew Mattina, Vincenzo Lomonaco, Clare D. Thiem, Benjamin R. Epstein
Design Principles for Lifelong Learning AI Accelerators. CoRR (2023)
Bradley H. Theilman, Yipu Wang, Ojas Parekh, William Severa, J. Darby Smith, James B. Aimone
Stochastic Neuromorphic Circuits for Solving MAXCUT. IPDPS (2023)
James B. Aimone, William Severa, J. Darby Smith
Synaptic Sampling of Neural Networks. ICRC (2023)
Suma George Cardwell, Catherine D. Schuman, J. Darby Smith, Karan Patel, Jaesuk Kwon, Samuel Liu, Christopher Allemang, Shashank Misra, Jean Anne Incorvia, James B. Aimone
Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation. ICRC (2022)
Craig M. Vineyard, Suma Cardwell, Frances S. Chance, Srideep Musuvathy, Fred Rothganger, William Severa, John Smith, Corinne Teeter, Felix Wang, James B. Aimone
Neural Mini-Apps as a Tool for Neuromorphic Computing Insight. NICE (2022)
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) (2022)
Suma George Cardwell, Catherine D. Schuman, J. Darby Smith, Karan Patel, Jaesuk Kwon, Samuel Liu, Christopher Allemang, Shashank Misra, Jean Anne Incorvia, James B. Aimone
Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation. CoRR (2022)
Jack Lindsey, James B. Aimone
Sequence Learning and Consolidation on Loihi using On-chip Plasticity. NICE (2022)
Jack Lindsey, James B. Aimone
Sequence Learning and Consolidation on Loihi using On-chip Plasticity. CoRR (2022)
James B. Aimone, Aaron J. Hill, William M. Severa, Craig M. Vineyard
Spiking Neural Streaming Binary Arithmetic. CoRR (2022)
Bradley H. Theilman, Yipu Wang, Ojas D. Parekh, William Severa, J. Darby Smith, James B. Aimone
Stochastic Neuromorphic Circuits for Solving MAXCUT. CoRR (2022)
J. Darby Smith, Aaron J. Hill, Leah E. Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas Parekh, William Severa, James B. Aimone
Neuromorphic scaling advantages for energy-efficient random walk computation. CoRR (2021)
James B. Aimone, Richard B. Lehoucq, William Severa, J. Darby Smith
Assessing a Neuromorphic Platform for use in Scientific Stochastic Sampling. ICRC (2021)
James B. Aimone, Yang Ho, Ojas Parekh, Cynthia A. Phillips, Ali Pinar, William Severa, Yipu Wang
Provable Advantages for Graph Algorithms in Spiking Neural Networks. SPAA (2021)
James B. Aimone
A Roadmap for Reaching the Potential of Brain-Derived Computing. Adv. Intell. Syst. 3 (1) (2021)
James B. Aimone, Aaron J. Hill, William M. Severa, Craig M. Vineyard
Spiking Neural Streaming Binary Arithmetic. ICRC (2021)
Frances S. Chance, James B. Aimone, Srideep Musuvathy, Michael R. Smith, Craig M. Vineyard, Felix Wang
Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence. Frontiers Comput. Neurosci. 14 (2020)
J. Darby Smith, William Severa, Aaron J. Hill, Leah Reeder, Brian Franke, Richard B. Lehoucq, Ojas D. Parekh, James B. Aimone
Solving a steady-state PDE using spiking networks and neuromorphic hardware. ICONS (2020)
Ojas Parekh, Cynthia A. Phillips, Conrad D. James, James B. Aimone
Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication. CoRR (2020)
J. Darby Smith, William Severa, Aaron J. Hill, Leah Reeder, Brian Franke, Richard B. Lehoucq, Ojas D. Parekh, James B. Aimone
Solving a steady-state PDE using spiking networks and neuromorphic hardware. CoRR (2020)
Suma George Cardwell, Craig M. Vineyard, William Severa, Frances S. Chance, Frederick H. Rothganger, Felix Wang, Srideep Musuvathy, Corinne Teeter, James B. Aimone
Truly Heterogeneous HPC: Co-design to Achieve What Science Needs from HPC. SMC (2020)
James B. Aimone, Yang Ho, Ojas Parekh, Cynthia A. Phillips, Ali Pinar, William Severa, Yipu Wang
Provable Neuromorphic Advantages for Computing Shortest Paths. SPAA (2020)
James B. Aimone, William Severa, Craig M. Vineyard
Composing Neural Algorithms with Fugu. CoRR (2019)
James B. Aimone
Neural algorithms and computing beyond Moore's law. Commun. ACM 62 (4) (2019)
James B. Aimone, Ojas Parekh, Cynthia A. Phillips, Ali Pinar, William Severa, Helen Xu
Dynamic Programming with Spiking Neural Computing. ICONS (2019)
Tu-Thach Quach, Sapan Agarwal, Conrad D. James, Matthew J. Marinella, James B. Aimone
Sparse Data Acquisition on Emerging Memory Architectures. IEEE Access 7 (2019)
William Severa, Craig M. Vineyard, Ryan Dellana, Stephen J. Verzi, James B. Aimone
Training deep neural networks for binary communication with the Whetstone method. Nat. Mach. Intell. 1 (2) (2019)
James B. Aimone, William Severa, Craig M. Vineyard
Composing neural algorithms with Fugu. ICONS (2019)
William Severa, Rich Lehoucq, Ojas Parekh, James B. Aimone
Spiking Neural Algorithms for Markov Process Random Walk. IJCNN (2018)
Aleksandra Faust, James B. Aimone, Conrad D. James, Lydia Tapia
Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting. CDC (2018)
Aleksandra Faust, James B. Aimone, Conrad D. James, Lydia Tapia
Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting. CoRR (2018)
Felix Wang, Tu-Thach Quach, Jason Wheeler, James B. Aimone, Conrad D. James
Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification. IEEE Trans. Inf. Forensics Secur. 13 (10) (2018)
Ojas Parekh, Cynthia A. Phillips, Conrad D. James, James B. Aimone
Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication. SPAA (2018)
Michael R. Smith, Joe Ingram, Christopher C. Lamb, Timothy Draelos, Justin E. Doak, James B. Aimone, Conrad D. James
Dynamic Analysis of Executables to Detect and Characterize Malware. ICMLA (2018)
Stephen J. Verzi, Fredrick H. Rothganger, Ojas Parekh, Tu-Thach Quach, Nadine E. Miner, Craig M. Vineyard, Conrad D. James, James B. Aimone
Computing with Spikes: The Advantage of Fine-Grained Timing. Neural Comput. 30 (10) (2018)
William Severa, Rich Lehoucq, Ojas Parekh, James B. Aimone
Spiking Neural Algorithms for Markov Process Random Walk. CoRR (2018)
William Severa, Craig M. Vineyard, Ryan Dellana, Stephen J. Verzi, James B. Aimone
Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication. CoRR (2018)
Kristofer E. Bouchard, James B. Aimone, Miyoung Chun, Thomas Dean, Michael Denker, Markus Diesmann, David Donofrio, Loren M. Frank, Narayanan Kasthuri, Christof Koch, Oliver Rübel, Horst D. Simon, Friedrich T. Sommer, Prabhat
International Neuroscience Initiatives through the Lens of High-Performance Computing. Computer 51 (4) (2018)
James B. Aimone
Exponential scaling of neural algorithms - a future beyond Moore's Law? CoRR (2017)
Justin E. Doak, Joe B. Ingram, Sam A. Mulder, John H. Naegle, Jonathan A. Cox, James B. Aimone, Kevin R. Dixon, Conrad D. James, David R. Follett
Tracking Cyber Adversaries with Adaptive Indicators of Compromise. CoRR (2017)
Aaron J. Hill, Jonathon W. Donaldson, Fredrick H. Rothganger, Craig M. Vineyard, David R. Follett, Pamela L. Follett, Michael R. Smith, Stephen J. Verzi, William Severa, Felix Wang, James B. Aimone, John H. Naegle, Conrad D. James
A Spike-Timing Neuromorphic Architecture. ICRC (2017)
James B. Aimone, Ojas Parekh, William Severa
Neural computing for scientific computing applications: more than just machine learning. NCS (2017)
William M. Severa, Jerilyn A. Timlin, Suraj Kholwadwala, Conrad D. James, James B. Aimone
Data-driven Feature Sampling for Deep Hyperspectral Classification and Segmentation. CoRR (2017)
James B. Aimone, William M. Severa
Context-modulation of hippocampal dynamics and deep convolutional networks. CoRR (2017)
Timothy J. Draelos, Nadine E. Miner, Christopher C. Lamb, Jonathan A. Cox, Craig M. Vineyard, Kristofor D. Carlson, William M. Severa, Conrad D. James, James B. Aimone
Neurogenesis deep learning: Extending deep networks to accommodate new classes. IJCNN (2017)
Stephen J. Verzi, Craig M. Vineyard, Eric D. Vugrin, Meghan A. Galiardi, Conrad D. James, James B. Aimone
Optimization-based computation with spiking neurons. IJCNN (2017)
William Severa, Ojas Parekh, Conrad D. James, James B. Aimone
A Combinatorial Model for Dentate Gyrus Sparse Coding. Neural Comput. 29 (1) (2017)
Michael R. Smith, Joe B. Ingram, Christopher C. Lamb, Timothy J. Draelos, Justin E. Doak, James B. Aimone, Conrad D. James
Dynamic Analysis of Executables to Detect and Characterize Malware. CoRR (2017)
David R. Follett, Duncan Townsend, Pamela L. Follett, Gabe D. Karpman, John H. Naegle, Roger A. Suppona, James B. Aimone, Conrad D. James
Neuromorphic data microscope. NCS (2017)
Michael R. Smith, Aaron J. Hill, Kristofor D. Carlson, Craig M. Vineyard, Jonathon Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James B. Aimone
A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines. CoRR (2017)
Michael R. Smith, Aaron J. Hill, Kristofor D. Carlson, Craig M. Vineyard, Jonathon Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James B. Aimone
A novel digital neuromorphic architecture efficiently facilitating complex synaptic response functions applied to liquid state machines. IJCNN (2017)
Craig M. Vineyard, Stephen J. Verzi, Conrad D. James, James B. Aimone
Quantifying neural information content: A case study of the impact of hippocampal adult neurogenesis. IJCNN (2016)
Timothy J. Draelos, Nadine E. Miner, Christopher C. Lamb, Craig M. Vineyard, Kristofor D. Carlson, Conrad D. James, James B. Aimone
Neurogenesis Deep Learning. CoRR (2016)
William Severa, Ojas Parekh, Kristofor D. Carlson, Conrad D. James, James B. Aimone
Spiking network algorithms for scientific computing. ICRC (2016)
Fred Rothganger, Conrad D. James, James B. Aimone
Computing with dynamical systems. ICRC (2016)
Fred Rothganger, Brian R. Evans, James B. Aimone, Erik P. DeBenedictis
Training neural hardware with noisy components. IJCNN (2015)
Craig M. Vineyard, Stephen J. Verzi, Conrad D. James, James B. Aimone, Gregory L. Heileman
Repeated play of the SVM game as a means of adaptive classification. IJCNN (2015)
Craig M. Vineyard, Stephen J. Verzi, Conrad D. James, James B. Aimone, Gregory L. Heileman
MapReduce SVM Game. INNS Conference on Big Data (2015)
Jonathan A. Cox, Conrad D. James, James B. Aimone
A Signal Processing Approach for Cyber Data Classification with Deep Neural Networks. Complex Adaptive Systems (2015)
James B. Aimone, Jason P. Weick
Perspectives for computational modeling of cell replacement for neurological disorders. Frontiers Comput. Neurosci. 7 (2013)
Craig M. Vineyard, Stephen J. Verzi, Thomas P. Caudell, Michael L. Bernard, James B. Aimone
Adult Neurogenesis: Implications on Human And Computational Decision Making. HCI (24) (2013)
Craig M. Vineyard, James B. Aimone, Glory R. Emmanuel
Neurogenesis in a High Resolution Dentate Gyrus Model. BICA (2012)
James B. Aimone, Sebastian Jessberger, Fred H. Gage
Adult neurogenesis. Scholarpedia 2 (2) (2007)