James B. Aimone

According to our database, James B. Aimone authored at least 64 papers between 2007 and 2023.

Collaborative distances:

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

2023

Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute.

James B. Aimone, Omar Awile, Markus Diesmann, James C. Knight, Thomas Nowotny, Felix Schürmann

Frontiers Neuroinformatics, March, 2023

Neuromorphic Co-Design as a Game.

Craig M. Vineyard, William M. Severa, James B. Aimone

CoRR, 2023

Is stochastic thermodynamics the key to understanding the energy costs of computation?

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

CoRR, 2023

Design Principles for Lifelong Learning AI Accelerators.

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

CoRR, 2023

Decomposing spiking neural networks with Graphical Neural Activity Threads.

Bradley H. Theilman, Felix Wang, Fred Rothganger, James B. Aimone

CoRR, 2023

Goemans-Williamson MAXCUT approximation algorithm on Loihi.

Bradley H. Theilman, James B. Aimone

Proceedings of the Neuro-Inspired Computational Elements Conference, 2023

Stochastic Neuromorphic Circuits for Solving MAXCUT.

Bradley H. Theilman, Yipu Wang, Ojas Parekh, William Severa, J. Darby Smith, James B. Aimone

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Synaptic Sampling of Neural Networks.

James B. Aimone, William Severa, J. Darby Smith

Proceedings of the IEEE International Conference on Rebooting Computing, 2023

Context Modulation Enables Multi-tasking and Resource Efficiency in Liquid State Machines.

Peter Helfer, Corinne Teeter, Aaron J. Hill, Craig M. Vineyard, James B. Aimone, Dhireesha Kudithipudi

Proceedings of the 2023 International Conference on Neuromorphic Systems, 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

Localization through Grid-basedEncodings on Digital Elevation Models.

Felix Wang, Corinne Teeter, Sarah Luca, Srideep Musuvathy, Brad Aimone

Proceedings of the NICE 2022: Neuro-Inspired Computational Elements Conference, 2022

Neural Mini-Apps as a Tool for Neuromorphic Computing Insight.

Craig M. Vineyard, Suma Cardwell, Frances S. Chance, Srideep Musuvathy, Fred Rothganger, William Severa, John Darby Smith, Corinne Teeter, Felix Wang, James B. Aimone

Proceedings of the NICE 2022: Neuro-Inspired Computational Elements Conference, 2022

Sequence Learning and Consolidation on Loihi using On-chip Plasticity.

Jack Lindsey, James B. Aimone

Proceedings of the NICE 2022: Neuro-Inspired Computational Elements Conference, 2022

Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation.

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

Proceedings of the IEEE International Conference on Rebooting Computing, 2022

Distributed Localization with Grid-based Representations on Digital Elevation Models.

Felix Wang, Corinne Teeter, Sarah Luca, Srideep Musuvathy, James Bradley Aimone

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

Learning to Parameterize a Stochastic Process Using Neuromorphic Data Generation.

William Severa, J. Darby Smith, James Bradley Aimone, Richard B. Lehoucq

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

2021

Neuromorphic scaling advantages for energy-efficient random walk computation.

J. Darby Smith, Aaron J. Hill, Leah E. Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas Parekh, William Severa, James B. Aimone

CoRR, 2021

A Roadmap for Reaching the Potential of Brain-Derived Computing.

James B. Aimone

Adv. Intell. Syst., 2021

Provable Advantages for Graph Algorithms in Spiking Neural Networks.

James B. Aimone, Yang Ho, Ojas Parekh, Cynthia A. Phillips, Ali Pinar, William Severa, Yipu Wang

Proceedings of the SPAA '21: 33rd ACM Symposium on Parallelism in Algorithms and Architectures, 2021

Assessing a Neuromorphic Platform for use in Scientific Stochastic Sampling.

James B. Aimone, Richard B. Lehoucq, William Severa, J. Darby Smith

Proceedings of the 2021 International Conference on Rebooting Computing (ICRC), Los Alamitos, CA, USA, November 30, 2021

Spiking Neural Streaming Binary Arithmetic.

James B. Aimone, Aaron J. Hill, William M. Severa, Craig M. Vineyard

Proceedings of the 2021 International Conference on Rebooting Computing (ICRC), Los Alamitos, CA, USA, November 30, 2021

2020

Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence.

Frances S. Chance, James B. Aimone, Srideep Musuvathy, Michael R. Smith, Craig M. Vineyard, Felix Wang

Frontiers Comput. Neurosci., 2020

Provable Neuromorphic Advantages for Computing Shortest Paths.

James B. Aimone, Yang Ho, Ojas Parekh, Cynthia A. Phillips, Ali Pinar, William Severa, Yipu Wang

Proceedings of the SPAA '20: 32nd ACM Symposium on Parallelism in Algorithms and Architectures, 2020

Truly Heterogeneous HPC: Co-design to Achieve What Science Needs from HPC.

Suma George Cardwell, Craig M. Vineyard, William Severa, Frances S. Chance, Fredrick H. Rothganger, Felix Wang, Srideep Musuvathy, Corinne Teeter, James B. Aimone

Proceedings of the Driving Scientific and Engineering Discoveries Through the Convergence of HPC, Big Data and AI, 2020

Evaluating complexity and resilience trade-offs in emerging memory inference machines.

Christopher H. Bennett, Ryan Dellana, T. Patrick Xiao, Ben Feinberg, Sapan Agarwal, Suma Cardwell, Matthew J. Marinella, William Severa, Brad Aimone

Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020

Solving a steady-state PDE using spiking networks and neuromorphic hardware.

J. Darby Smith, William Severa, Aaron J. Hill, Leah Reeder, Brian Franke, Richard B. Lehoucq, Ojas D. Parekh, James B. Aimone

Proceedings of the International Conference on Neuromorphic Systems, 2020

2019

Training deep neural networks for binary communication with the Whetstone method.

William Severa, Craig M. Vineyard, Ryan Dellana, Stephen J. Verzi, James B. Aimone

Nat. Mach. Intell., 2019

Neural algorithms and computing beyond Moore's law.

James B. Aimone

Commun. ACM, 2019

Sparse Data Acquisition on Emerging Memory Architectures.

Tu-Thach Quach, Sapan Agarwal, Conrad D. James, Matthew J. Marinella, James B. Aimone

IEEE Access, 2019

Composing neural algorithms with Fugu.

James B. Aimone, William Severa, Craig M. Vineyard

Proceedings of the International Conference on Neuromorphic Systems, 2019

Dynamic Programming with Spiking Neural Computing.

James B. Aimone, Ojas Parekh, Cynthia A. Phillips, Ali Pinar, William Severa, Helen Xu

Proceedings of the International Conference on Neuromorphic Systems, 2019

2018

Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification.

Felix Wang, Tu-Thach Quach, Jason Wheeler, James B. Aimone, Conrad D. James

IEEE Trans. Inf. Forensics Secur., 2018

Computing with Spikes: The Advantage of Fine-Grained Timing.

Stephen J. Verzi, Fredrick H. Rothganger, Ojas Parekh, Tu-Thach Quach, Nadine E. Miner, Craig M. Vineyard, Conrad D. James, James B. Aimone

Neural Comput., 2018

Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication.

William Severa, Craig M. Vineyard, Ryan Dellana, Stephen J. Verzi, James B. Aimone

CoRR, 2018

International Neuroscience Initiatives through the Lens of High-Performance Computing.

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

Computer, 2018

Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication.

Ojas Parekh, Cynthia A. Phillips, Conrad D. James, James B. Aimone

Proceedings of the 30th on Symposium on Parallelism in Algorithms and Architectures, 2018

Spiking Neural Algorithms for Markov Process Random Walk.

William Severa, Rich Lehoucq, Ojas Parekh, James B. Aimone

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Dynamic Analysis of Executables to Detect and Characterize Malware.

Michael R. Smith, Joe Ingram, Christopher C. Lamb, Timothy Draelos, Justin E. Doak, James B. Aimone, Conrad D. James

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting.

Aleksandra Faust, James B. Aimone, Conrad D. James, Lydia Tapia

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

A Combinatorial Model for Dentate Gyrus Sparse Coding.

William Severa, Ojas Parekh, Conrad D. James, James B. Aimone

Neural Comput., 2017

Tracking Cyber Adversaries with Adaptive Indicators of Compromise.

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

CoRR, 2017

Context-modulation of hippocampal dynamics and deep convolutional networks.

James B. Aimone, William M. Severa

CoRR, 2017

Data-driven Feature Sampling for Deep Hyperspectral Classification and Segmentation.

William M. Severa, Jerilyn A. Timlin, Suraj Kholwadwala, Conrad D. James, James B. Aimone

CoRR, 2017

A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines.

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

CoRR, 2017

Exponential scaling of neural algorithms - a future beyond Moore's Law?

James B. Aimone

CoRR, 2017

Neuromorphic data microscope.

David R. Follett, Duncan Townsend, Pamela L. Follett, Gabe D. Karpman, John H. Naegle, Roger A. Suppona, James B. Aimone, Conrad D. James

Proceedings of the Neuromorphic Computing Symposium, 2017

Neural computing for scientific computing applications: more than just machine learning.

James B. Aimone, Ojas Parekh, William Severa

Proceedings of the Neuromorphic Computing Symposium, 2017

Optimization-based computation with spiking neurons.

Stephen J. Verzi, Craig M. Vineyard, Eric D. Vugrin, Meghan A. Galiardi, Conrad D. James, James B. Aimone

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

A novel digital neuromorphic architecture efficiently facilitating complex synaptic response functions applied to liquid state machines.

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

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Neurogenesis deep learning: Extending deep networks to accommodate new classes.

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

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

A Spike-Timing Neuromorphic Architecture.

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

Proceedings of the IEEE International Conference on Rebooting Computing, 2017

2016

Neurogenesis Deep Learning.

Timothy J. Draelos, Nadine E. Miner, Christopher C. Lamb, Craig M. Vineyard, Kristofor D. Carlson, Conrad D. James, James B. Aimone

CoRR, 2016

Quantifying neural information content: A case study of the impact of hippocampal adult neurogenesis.

Craig M. Vineyard, Stephen J. Verzi, Conrad D. James, James B. Aimone

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

Spiking network algorithms for scientific computing.

William Severa, Ojas Parekh, Kristofor D. Carlson, Conrad D. James, James B. Aimone

Proceedings of the IEEE International Conference on Rebooting Computing, 2016

Computing with dynamical systems.

Fred Rothganger, Conrad D. James, James B. Aimone

Proceedings of the IEEE International Conference on Rebooting Computing, 2016

2015

MapReduce SVM Game.

Craig M. Vineyard, Stephen J. Verzi, Conrad D. James, James B. Aimone, Gregory L. Heileman

Proceedings of the INNS Conference on Big Data 2015, 2015

Repeated play of the SVM game as a means of adaptive classification.

Craig M. Vineyard, Stephen J. Verzi, Conrad D. James, James B. Aimone, Gregory L. Heileman

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Training neural hardware with noisy components.

Fred Rothganger, Brian R. Evans, James B. Aimone, Erik P. DeBenedictis

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

A Signal Processing Approach for Cyber Data Classification with Deep Neural Networks.

Jonathan A. Cox, Conrad D. James, James B. Aimone

Proceedings of the Complex Adaptive Systems 2015 Conference, San Jose, 2015

2014

Memristors as Synapses in Artificial Neural Networks: Biomimicry Beyond Weight Change.

Andrew J. Lohn, Patrick R. Mickel, James B. Aimone, Erik P. DeBenedictis, Matthew J. Marinella

Proceedings of the Cybersecurity Systems for Human Cognition Augmentation, 2014

2013

Perspectives for computational modeling of cell replacement for neurological disorders.

James B. Aimone, Jason P. Weick

Frontiers Comput. Neurosci., 2013

Adult Neurogenesis: Implications on Human And Computational Decision Making.

Craig M. Vineyard, Stephen J. Verzi, Thomas P. Caudell, Michael L. Bernard, James B. Aimone

Proceedings of the Foundations of Augmented Cognition, 2013

2012

Neurogenesis in a High Resolution Dentate Gyrus Model.

Craig M. Vineyard, James B. Aimone, Glory R. Emmanuel

Proceedings of the Biologically Inspired Cognitive Architectures 2012 - Proceedings of the Third Annual Meeting of the BICA Society, Palermo, Sicily, Italy, October 31, 2012

2007

Adult neurogenesis.

James B. Aimone, Sebastian Jessberger, Fred H. Gage

Scholarpedia, 2007