default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDICONS 2024: Arlington, VA, USA
- International Conference on Neuromorphic Systems, ICONS 2024, Arlington, VA, USA, July 30 - Aug. 2, 2024. IEEE 2024, ISBN 979-8-3503-6865-9
- Michael J. Smith, Michael A. Temple, James W. Dean:
Edge Device CNN Classification Using Eventized RF Fingerprints. 1-8 - Alireza Raisiardali, Muhammad Ali Siddiqi, Christos Strydis, Said Hamdioui, Dante Gabriel Muratore, Rajendra Bishnoi:
Real-Time Supervised Spiking Neural Network for Cerebellar Purkinje Cells Spike Detection and Classification. 9-15 - Yuzhen Ke, Zoran Utkovski, Mehdi Heshmati, Osvaldo Simeone, Johannes Dommel, Slawomir Stanczak:
Neuromorphic Wireless Device-Edge Co-Inference via the Directed Information Bottleneck. 16-23 - Yi Jiang, Sen Lu, Abhronil Sengupta:
Stochastic Spiking Neural Networks with First-to-Spike Coding. 24-31 - Harshvardhan Uppaluru
, Md. Mehedi Hasan Tanim, Md. Omar Faruque, Mohammed Rafeeq Khan, Zoe Templin, Feng Zhao, Jinhui Wang:
Variation-Aware Non-linear Mapping for Honey-Memristor Based Neuromorphic System. 32-38 - Shadi Matinizadeh, Arghavan Mohammadhassani, Noah Pacik-Nelson, Ioannis Polykretis, Krupa Tishbi, Suman Kumar, M. Lakshmi Varshika, Abhishek Kumar Mishra, Nagarajan Kandasamy, James A. Shackleford, Eric M. Gallo, Anup Das:
Neuromorphic Computing for the Masses. 39-46 - Simon Janssen, Stijn Groenen, Simon Reichert, Johan Kwisthout:
Solving Minimum Spanning Tree Problem in Spiking Neural Networks: Improved Results. 47-54 - Thomas Firmin, Pierre Boulet, El-Ghazali Talbi:
Asynchronous Multi-Fidelity Hyperparameter Optimization of Spiking Neural Networks. 55-62 - Narasinga Rao Miniskar, Aaron R. Young, Kazi Asifuzzaman, Shruti R. Kulkarni, Prasanna Date, Alice Bean, Jeffrey S. Vetter:
Neuro-Spark: A Submicrosecond Spiking Neural Networks Architecture for In-Sensor Filtering. 63-70 - James Seekings, Peyton Chandarana, Mahsa Ardakani, Mohammadreza Mohammadi, Ramtin Zand:
Towards Efficient Deployment of Hybrid SNNs on Neuromorphic and Edge AI Hardware. 71-77 - Anmol Biswas, Sharvari Ashok Medhe, Raghav Singhal, Udayan Ganguly:
Temporal and Spatial Reservoir Ensembling Techniques for Liquid State Machines. 78-81 - Irene Ambrosini, Luna Gava, Massimiliano Iacono, Arren Glover, Madeleine Bartlett, Terrence C. Stewart, Chiara Bartolozzi:
Timing Actions in Games Through Bio-Inspired Reinforcement Learning. 82-89 - Erika Schmitt, Sanchit Gupta, Patrick Abbs:
Continuous Learning for Real-Time Auditory Blind Source Separation Applications. 90-93 - Cina Arjmand, Yingfu Xu, Kevin Shidqi, Alexandra F. Dobrita, Kanishkan Vadivel, Paul Detterer, Manolis Sifalakis, Amirreza Yousefzadeh, Guangzhi Tang:
TRIP: Trainable Region-of-Interest Prediction for Hardware-Efficient Neuromorphic Processing on Event-Based Vision. 94-101 - Nicholas J. Pritchard, Andreas Wicenec, Mohammed Bennamoun, Richard Dodson:
Supervised Radio Frequency Interference Detection with SNNs. 102-109 - Paola Vitolo, George Psaltakis, Michael A. Tomlinson, Gian Domenico Licciardo, Andreas G. Andreou:
Natural Language to Verilog: Design of a Recurrent Spiking Neural Network using Large Language Models and ChatGPT. 110-116 - Jiaxin Huang, Bernhard Vogginger, Florian Kelber, Hector A. Gonzalez, Klaus Knobloch, Christian Georg Mayr:
Fast Switching Serial and Parallel Paradigms of SNN Inference on Multi-Core Heterogeneous Neuromorphic Platform SpiNNaker2. 117-123 - Mark Schöne, Neeraj Mohan Sushma, Jingyue Zhuge, Christian Mayr, Anand Subramoney, David Kappel:
Scalable Event-by-Event Processing of Neuromorphic Sensory Signals with Deep State-Space Models. 124-131 - Rishav Mukherji, Mark Schöne, Khaleelulla Khan Nazeer, Christian Mayr, David Kappel, Anand Subramoney:
Weight Sparsity Complements Activity Sparsity in Neuromorphic Language Models. 132-139 - Jann Krausse, Sven Nitzsche, Brian Pachideh, Carmen Weigelt, Klaus Knobloch, Jürgen Becker:
Exploring Neuronal Leakage for Spiking Neural Networks on Event-Driven Hardware. 140-147 - Ahmed Hasssan, Jian Meng, Anupreetham Anupreetham, Jae-sun Seo:
IM-SNN: Memory-Efficient Spiking Neural Network with Low-Precision Membrane Potentials and Weights. 148-155 - Felix Wang, William Severa:
Using STACS as a High-Performance Simulation Backend for Fugu. 156-160 - Craig M. Vineyard, William M. Severa, James B. Aimone:
Strategic Considerations for Neuromorphic Computing. 161-168 - Muath Abu Lebdeh, Kasim Sinan Yildirim, Davide Brunelli:
Per Layer Specialization for Memory-Efficient Spiking Neural Networks. 169-176 - Fredrik Sandin, Ulf Bodin, Anders Lindgren, Olov Schelén:
Digital Computing Continuum Abstraction for Neuromorphic Systems. 177-184 - Nikhil Garg, Davide Florini, Patrick Dufour, Eloir Muhr, Mathieu-Coumba Faye, Marc Bocquet, Damien Querlioz, Yann Beilliard, Dominique Drouin, Fabien Alibart, Jean-Michel Portal:
Versatile CMOS Analog LIF Neuron for Memristor-Integrated Neuromorphic Circuits. 185-192 - G. William Chapman, Andrew S. Alexander, Frances S. Chance, Michael E. Hasselmo:
Self-Supervised Mapping and Localization by Predictive Learning. 193-200 - Cody Scharzenberger, Shay Snyder, Sumedh R. Risbud, Joe Hays, Maryam Parsa:
Learning to Estimate Regions of Attraction of Autonomous Dynamical Systems Using Bayesian Physics Informed Neural Networks. 201-208 - Ashish Gautam, Takashi Kohno, Prasanna Date, Robert M. Patton, Thomas E. Potok:
A Suppression-based STDP Rule Resilient to Jitter Noise in Spike Patterns for Neuromorphic Computing. 209-216 - Jeelka Solanki, Jacob Pelton, Rocco Febbo, Maximilian Liehr, Andrew DeCandia, Karsten Beckmann, Garrett S. Rose, Nathaniel C. Cady:
In-Memory Computation Using CMOS-Integrated Resistive RAM for Robotic Navigation. 217-223 - Kendric Hood, Ang Li, Qiang Guan:
SNNPG: Using Spiking Neural Networks to Detect Attacks in the Power Grid. 224-228 - Jack Hutchins, Diego Ferrer, James Fillers, Catherine D. Schuman:
Black-Box Adversarial Attacks on Spiking Neural Network for Time Series Data. 229-233 - Ryan O'Loughlin, Bryce A. Primavera, Jeffrey Shainline:
Spatiotemporal Dendritic Processing in Superconducting Optoelectronic Networks. 234-241 - Luke McCombs, Drew Friend, Luke Whatley, Catherine D. Schuman:
Competitive Co-Evolution with Spiking Neural Networks. 242-246 - Jeffrey M. Shainline, Bryce A. Primavera, Ryan O'Loughlin:
Modeling Spiking Neurons Without Spikes. 247-250 - Jamie Lohoff, Jan Finkbeiner, Emre Neftci:
SNNAX - Spiking Neural Networks in JAX. 251-255 - Jason Sinaga, Victoria Clerico, Md. Abdullah-Al Kaiser, Shay Snyder, Arya Lohia, Gregory Schwartz, Maryam Parsa, Akhilesh Jaiswal:
Hardware-Algorithm Re-Engineering of Retinal Circuit for Intelligent Object Motion Segmentation. 256-263 - Thomas M. Summe, Clemens JS Schaefer, Siddharth Joshi:
Estimating Post-Synaptic Effects for Online Training of Feed-Forward SNNs. 264-271 - Malyaban Bal, Yi Jiang, Abhronil Sengupta:
Exploring Extreme Quantization in Spiking Language Models. 272-276 - Bryce A. Primavera, Saeed Khan, Samuel R. Adler, Jeffrey M. Shainline:
Programmable Synapses and Dendritic Circuits for Superconducting Optoelectronic Neuromorphic Computing. 277-281 - Derek Gobin, Shay Snyder, Guojing Cong, Shruti R. Kulkarni, Catherine D. Schuman, Maryam Parsa:
Exploration of Novel Neuromorphic Methodologies for Materials Applications. 282-286 - Hamed Poursiami, Ihsen Alouani, Maryam Parsa:
Watermarking Neuromorphic Brains: Intellectual Property Protection in Spiking Neural Networks. 287-294 - Shay Snyder, Derek Gobin, Victoria Clerico, Sumedh R. Risbud, Maryam Parsa:
Parallelized Multi-Agent Bayesian Optimization in Lava. 295-298 - Tianze Liu, Md Abu Bakr Siddique, Hongyu An:
Mimicking Associative Learning of Rats via a Neuromorphic Robot in Open Field Maze Using Spatial Cell Models. 299-306 - Yang Ho, Armida Carbajal, Leonardo Escamilla, Ali Pinar:
Neuromorphic Monte Carlo Tree Search Methods for Shortest Path Interdiction. 307-311 - Jiaqi Lin, Malyaban Bal, Abhronil Sengupta:
Scaling SNNs Trained Using Equilibrium Propagation to Convolutional Architectures. 312-318 - Kevin Zhu, Connor Mattson, Shay Snyder, Ricardo Vega, Daniel S. Brown, Maryam Parsa, Cameron Nowzari:
Spiking Neural Networks as a Controller for Emergent Swarm Agents. 319-326 - Junghoon Chae, Seung-Hwan Lim, Shruti R. Kulkarni, Catherine D. Schuman:
SNNVis: Visualizing Graph Embedding of Evolutionary Optimization for Spiking Neural Networks. 327-330 - Tokey Tahmid, Mark Gates, Piotr Luszczek, Catherine D. Schuman:
Towards Scalable and Efficient Spiking Reinforcement Learning for Continuous Control Tasks. 331-335 - Md Tawsif Rahman Chowdhury, Huynh Quang Nguyen Vo, Paritosh Ramanan, Murat Yildirim, Gozde Tutuncuoglu:
The Lynchpin of In-Memory Computing: A Benchmarking Framework for Vector-Matrix Multiplication in RRAMs. 336-342 - Luke Parker, Suma George Cardwell, Frances S. Chance, Scott Koziol:
Bio-Inspired Active Silicon Dendrite for Direction Selectivity. 343-349 - Sarah Luca, Felix Wang, Srideep Musuvathy:
A Spiking Neuromorphic Algorithm for Markov Reward Processes. 350-357 - Steven Abreu, Jens Egholm Pedersen:
Neuromorphic Programming: Emerging Directions for Brain-Inspired Hardware. 358-365 - Florian Feiler, Emre Neftci, Younes Bouhadjar:
Unsupervised Learning of Spatio-Temporal Patterns in Spiking Neuronal Networks. 366-370 - Shanmuga Venkatachalam, Harideep Nair, Prabhu Vellaisamy, Yongqi Zhou, Ziad Youssfi, John Paul Shen:
Realtime Person Identification via Gait Analysis Using IMU Sensors on Edge Devices. 371-375 - Gauthier Boeshertz, Giacomo Indiveri, Manu V. Nair, Alpha Renner:
Accurate Mapping of RNNs on Neuromorphic Hardware with Adaptive Spiking Neurons. 376-380
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.
last updated on 2025-10-31 00:53 CET 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:
