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ORCIDICONS 2023: Santa Fe, NM, USA
- 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 - Samuel Schmidgall
, Joe Hays:
Synaptic motor adaptation: A three-factor learning rule for adaptive robotic control in spiking neural networks. 1:1-1:9 - Stein Stroobants, Christophe De Wagter, Guido de Croon:
Neuromorphic Control using Input-Weighted Threshold Adaptation. 2:1-2:8 - 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. 3:1-3:8 - Ryan O'Loughlin, Bryce A. Primavera, Jeffrey Shainline:
Dendritic Learning in Superconducting Optoelectronic Networks. 4:1-4:8 - Vijay Shankaran Vivekanand, Samarth Chopra, Shahin Hashemkhani, Rajkumar Chinnakonda Kubendran:
Robot Locomotion through Tunable Bursting Rhythms using Efficient Bio-mimetic Neural Networks on Loihi and Arduino Platforms. 5:1-5:7 - Simon Roy, François-Michel De Rainville, Marc-Antoine Drouin, Simon Savary, Terrence C. Stewart:
Event-based stereopsis with wearable stereo vision demonstrator. 6:1-6:4 - Terrence C. Stewart, Marc-Antoine Drouin, Michel Picard, Frank Billy Djupkep Dizeu, Antony Orth, Guillaume Gagné:
Using neuromorphic cameras to track quadcopters. 7:1-7:5 - Yi Tian, Juan Andrade-Cetto:
Egomotion from event-based SNN optical flow. 8:1-8:8 - Shay Snyder, Sumedh R. Risbud, Maryam Parsa:
Neuromorphic Bayesian Optimization in Lava. 9:1-9:5 - Charles Rizzo, Luke Mccombs, Braxton Haynie, Catherine D. Schuman, James S. Plank:
DVSGesture Recognition with Neuromorphic Observation Space Reduction Techniques. 10:1-10:8 - Gintautas Palinauskas, Camilo Amaya, Evan Eames, Michael Neumeier, Axel von Arnim:
Generating Event-Based Datasets for Robotic Applications using MuJoCo-ESIM. 11:1-11:7 - Hitesh Ahuja, Rajkumar Kubendran:
High-resolution Extreme-throughput Event-based Cameras using GALS Data-scanning Architecture. 12:1-12:6 - 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. 13:1-13:7 - Lillian Sharpe, Julia Steed, Md. Mazharul Islam, Ahmedullah Aziz, Catherine D. Schuman:
Impact of Neuron Firing Rate on Application and Algorithm Performance. 14:1-14:4 - Gavin Parpart, Sumedh R. Risbud, Garrett T. Kenyon, Yijing Watkins:
Implementing and Benchmarking the Locally Competitive Algorithm on the Loihi 2 Neuromorphic Processor. 15:1-15:6 - Jamie Lohoff, Zhenming Yu, Jan Finkbeiner, Anil Kaya, Kenneth Michael Stewart, Hin Wai Lui, Emre Neftci:
Interfacing Neuromorphic Hardware with Machine Learning Frameworks - A Review. 16:1-16:8 - 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. 17:1-17:9 - Zaidao Mei, Boyu Wang, Daniel Patrick Rider, Qinru Qiu:
SEnsitivity Modulated Importance Networking and Rehearsal for Spike Domain Incremental Learning. 18:1-18:8 - James A. Boyle, Mark Plagge, Suma George Cardwell, Frances S. Chance, Andreas Gerstlauer:
Performance and Energy Simulation of Spiking Neuromorphic Architectures for Fast Exploration. 19:1-19:4 - Mike Stuck, Richard Naud:
Burstprop for Learning in Spiking Neuromorphic Hardware. 20:1-20:5 - Hongyi Li, Mingkun Xu, Jing Pei, Rong Zhao:
Efficient GCN Deployment with Spiking Property on Spatial-Temporal Neuromorphic Chips. 21:1-21:8 - Jeff Orchard, Russell Jarvis:
Hyperdimensional Computing with Spiking-Phasor Neurons. 22:1-22:7 - Edoardo W. Grappolini, Anand Subramoney:
Beyond Weights: Deep learning in Spiking Neural Networks with pure synaptic-delay training. 23:1-23:4 - Shay Snyder, Kevin Zhu, Ricardo Vega, Cameron Nowzari, Maryam Parsa:
Zespol: A Lightweight Environment for Training Swarming Agents. 24:1-24:5 - Raphael Norman-Tenazas, Isaac Western, Gautam K. Vallabha, Matthew J. Roos, Erik C. Johnson, Brian S. Robinson:
Enabling local learning for generative-replay-based continual learning with a recurrent model of the insect memory center. 25:1-25:7 - Wilkie Olin-Ammentorp:
Sparsifying Spiking Networks through Local Rhythms. 26:1-26:4 - Melika Payvand, Simone D'Agostino, Filippo Moro, Yigit Demirag, Giacomo Indiveri, Elisa Vianello:
Dendritic Computation through Exploiting Resistive Memory as both Delays and Weights. 27:1-27:4 - Juan Pablo Romero Bermudez, Luis A. Plana, Andrew Rowley, Mikael Hessel, Jens Egholm Pedersen, Steve B. Furber, Jörg Conradt:
A High-Throughput Low-Latency Interface Board for SpiNNaker-in-the-loop Real-Time Systems. 28:1-28:8 - Ming-Jay Yang, John Paul Strachan:
State-Space Modeling and Tuning of Memristors for Neuromorphic Computing Applications. 29:1-29:8 - Jimmy Weber, Chenxi Wu, Melika Payvand:
GMap : An Open-source Efficient Compiler for Mapping any Network onto any Neuromophic Chip. 30:1-30:4 - Ruomin Zhu, Jason Eshraghian, Zdenka Kuncic:
Memristive Reservoirs Learn to Learn. 31:1-31:7 - Anindya Ghosh, Thomas Nowotny, James C. Knight:
Insect-inspired Spatio-temporal Downsampling of Event-based Input. 32:1-32:5 - Ole Richter, Hugh Greatorex, Benjamin Hucko, Madison Cotteret, Willian Soares Girão, Ella Janotte, Michele Mastella, Elisabetta Chicca:
A Subthreshold Second-Order Integration Circuit for Versatile Synaptic Alpha Kernel and Trace Generation. 33:1-33:4 - Michele Mastella, Hugh Greatorex, Madison Cotteret, Ella Janotte, Willian Soares Girão, Ole Richter, Elisabetta Chicca:
Synaptic Normalisation for On-Chip Learning in Analog CMOS Spiking Neural Networks. 34:1-34:4 - Suma George Cardwell, Frances S. Chance:
Dendritic Computation for Neuromorphic Applications. 35:1-35:5 - Alexander James White, Chou P. Hung, Andre V. Harrison, Chung-Chuan Lo:
Neuromorphic luminance-edge contextual preprocessing of naturally obscured targets. 36:1-36:8 - Douglas Cale Crowder, John Darby Smith, Suma George Cardwell:
Deep Reinforcement Learning Methods for Discovering Novel Neuromorphic Devices. 37:1-37:8 - Kyle Henke, Elijah Pelofske, Georg Hahn, Garrett T. Kenyon:
Sampling binary sparse coding QUBO models using a spiking neuromorphic processor. 38:1-38:5 - 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. 39:1-39:6 - Prasanna Date, Chathika Gunaratne, Shruti R. Kulkarni, Robert M. Patton, Mark Coletti, Thomas E. Potok:
SuperNeuro: A Fast and Scalable Simulator for Neuromorphic Computing. 40:1-40:4 - Melvin Estuardo Galicia, Ibrahim Jimale Osman, Christian Owusu-Afriyie, Rainer Leupers:
"S3cure": Scramble, Shuffle and Shambles - Secure Deployment of Weight Matrices in Memristor Crossbar Arrays. 41:1-41:8 - William Severa, Suma George Cardwell, Michael Krygier, Fredrick H. Rothganger, Craig Michael Vineyard:
Neuromorphic Population Evaluation using the Fugu Framework. 42:1-42:7
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