Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time

23 May 2025

Papers citing "Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time"

39 / 39 papers shown

Title
Deep Networks Always Grok and Here is Why Ahmed Imtiaz Humayun Randall Balestriero Richard Baraniuk AAML OOD AI4CE 110 23 0 23 Feb 2024
Efficient and Effective Time-Series Forecasting with Spiking Neural Networks Changze Lv Yansen Wang Dongqi Han Xiaoqing Zheng Xuanjing Huang Dongsheng Li AI4TS TPM 101 8 0 02 Feb 2024
SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence Wei Fang Yanqing Chen Jianhao Ding Zhaofei Yu T. Masquelier Ding Chen Liwei Huang Huihui Zhou Guoqi Li Yonghong Tian 75 226 0 25 Oct 2023
High-performance deep spiking neural networks with 0.3 spikes per neuron A. Stanojević Stanislaw Wo'zniak G. Bellec G. Cherubini A. Pantazi W. Gerstner 75 18 0 14 Jun 2023
Direct Learning-Based Deep Spiking Neural Networks: A Review Yu-Zhu Guo Xuhui Huang Zhe Ma AI4CE 105 52 0 31 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 141 37 0 29 Apr 2023
Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies Wei Fang Zhaofei Yu Zhaokun Zhou Ding Chen Yanqing Chen Zhengyu Ma T. Masquelier Yonghong Tian 57 42 0 25 Apr 2023
Spiking neural networks for nonlinear regression Alexander Henkes Jason K. Eshraghian Henning Wessels 69 29 0 06 Oct 2022
On the Intrinsic Structures of Spiking Neural Networks Shao-Qun Zhang Jia-Yi Chen Jin-Hui Wu Gao Zhang Huan Xiong Bin Gu Zhiping Zhou 29 2 0 21 Jun 2022
Neural Architecture Search for Spiking Neural Networks Youngeun Kim Yuhang Li Hyoungseob Park Yeshwanth Venkatesha Priyadarshini Panda 92 92 0 23 Jan 2022
Neural networks with linear threshold activations: structure and algorithms Sammy Khalife Hongyu Cheng A. Basu 71 16 0 15 Nov 2021
Efficient Neuromorphic Signal Processing with Loihi 2 Garrick Orchard E. P. Frady D. B. Rubin Sophia Sanborn S. Shrestha Friedrich T. Sommer Mike Davies 69 171 0 05 Nov 2021
Training Spiking Neural Networks Using Lessons From Deep Learning Jason K. Eshraghian Max Ward Emre Neftci Xinxin Wang Gregor Lenz Girish Dwivedi Bennamoun Doo Seok Jeong Wei D. Lu 70 449 0 27 Sep 2021
On transversality of bent hyperplane arrangements and the topological expressiveness of ReLU neural networks J. E. Grigsby Kathryn A. Lindsey 40 29 0 20 Aug 2020
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks Wei Fang Zhaofei Yu Yanqing Chen T. Masquelier Tiejun Huang Yonghong Tian 139 526 0 11 Jul 2020
Fast and energy-efficient neuromorphic deep learning with first-spike times Julian Goltz Laura Kriener A. Baumbach Sebastian Billaudelle O. Breitwieser ... Á. F. Kungl Walter Senn Johannes Schemmel K. Meier Mihai A. Petrovici 87 131 0 24 Dec 2019
Temporal Coding in Spiking Neural Networks with Alpha Synaptic Function: Learning with Backpropagation Iulia Comsa Krzysztof Potempa Luca Versari T. Fischbacher Andrea Gesmundo J. Alakuijala 70 178 0 30 Jul 2019
Deep Network Approximation Characterized by Number of Neurons Zuowei Shen Haizhao Yang Shijun Zhang 56 184 0 13 Jun 2019
Deep ReLU Networks Have Surprisingly Few Activation Patterns Boris Hanin David Rolnick 81 227 0 03 Jun 2019
The Geometry of Deep Networks: Power Diagram Subdivision Randall Balestriero Romain Cosentino B. Aazhang Richard Baraniuk AI4CE 51 64 0 21 May 2019
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs Gitta Kutyniok P. Petersen Mones Raslan R. Schneider 80 198 0 31 Mar 2019
$Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms$ Error bounds for approximations with deep ReLU neural networks in $W^{s,p}$ norms Ingo Gühring Gitta Kutyniok P. Petersen 86 199 0 21 Feb 2019
Surrogate Gradient Learning in Spiking Neural Networks Emre Neftci Hesham Mostafa Friedemann Zenke 90 1,237 0 28 Jan 2019
Complexity of Linear Regions in Deep Networks Boris Hanin David Rolnick 44 232 0 25 Jan 2019
Direct Training for Spiking Neural Networks: Faster, Larger, Better Yujie Wu Lei Deng Guoqi Li Jun Zhu Luping Shi 73 656 0 16 Sep 2018
Universality of Deep Convolutional Neural Networks Ding-Xuan Zhou HAI PINN 412 514 0 28 May 2018
Bounding and Counting Linear Regions of Deep Neural Networks Thiago Serra Christian Tjandraatmadja Srikumar Ramalingam MLT 65 250 0 06 Nov 2017
Optimal approximation of piecewise smooth functions using deep ReLU neural networks P. Petersen Felix Voigtländer 223 475 0 15 Sep 2017
The Expressive Power of Neural Networks: A View from the Width Zhou Lu Hongming Pu Feicheng Wang Zhiqiang Hu Liwei Wang 99 894 0 08 Sep 2017
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations Boris Hanin 59 355 0 09 Aug 2017
Optimal Approximation with Sparsely Connected Deep Neural Networks Helmut Bölcskei Philipp Grohs Gitta Kutyniok P. Petersen 197 255 0 04 May 2017
Understanding Deep Neural Networks with Rectified Linear Units R. Arora A. Basu Poorya Mianjy Anirbit Mukherjee PINN 146 641 0 04 Nov 2016
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 195 1,227 0 03 Oct 2016
Training Deep Spiking Neural Networks using Backpropagation Junhaeng Lee T. Delbruck Michael Pfeiffer 90 945 0 31 Aug 2016
Supervised learning based on temporal coding in spiking neural networks Hesham Mostafa 77 355 0 27 Jun 2016
On the Expressive Power of Deep Neural Networks M. Raghu Ben Poole Jon M. Kleinberg Surya Ganguli Jascha Narain Sohl-Dickstein 61 788 0 16 Jun 2016
Benefits of depth in neural networks Matus Telgarsky 356 608 0 14 Feb 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 323 18,625 0 06 Feb 2015
On the Number of Linear Regions of Deep Neural Networks Guido Montúfar Razvan Pascanu Kyunghyun Cho Yoshua Bengio 88 1,254 0 08 Feb 2014