Extending a Formal Model of Predictive Coding to Human Spoken Word Recognition [0.03%]
扩展形式预测编码模型以适用于人类口语单词识别
Bryce Rogers,Monica Yi-Chen Li,Thomas Hannagan et al.
Bryce Rogers et al.
There is a general consensus in theories of human speech recognition that humans engage in predictive processing during online speech processing. There are also claims that predictive processing is indicative of the operation of a predictiv...
Travis Monk,Shivaram Mani,Paul Hurley et al.
Travis Monk et al.
Sensory pathways differ widely across species and modalities in anatomy and function. Yet many solve variants of the same ancient, pervasive problem: quickly detecting meaningful changes in the world. Sometimes animals need to make these de...
Twin Network Augmentation: A Novel Training Strategy for Improved Spiking Neural Networks and Weight Quantization [0.03%]
双网增强：一种改进脉冲神经网络和权重量化的新型训练策略
Lucas Deckers,Benjamin Vandersmissen,Ing Jyh Tsang et al.
Lucas Deckers et al.
The proliferation of artificial neural networks (ANNs) has led to increased energy consumption, raising concerns about their sustainability. Spiking neural networks (SNNs) operate using sparse, binary spikes to communicate information betwe...
Teaching Signal Synchronization in Deep Neural Networks With Prospective Neurons [0.03%]
具有前瞻性神经元的深度神经网络中信号同步的教学
Nicolas Zucchet,Qianqian Feng,Axel Laborieux et al.
Nicolas Zucchet et al.
Working memory requires the brain to maintain information from the recent past to guide ongoing behavior. Neurons can contribute to this capacity by slowly integrating their inputs over time, creating persistent activity that outlasts the o...
Peter Kirby,Laura Smets,Werner Van Leekwijck et al.
Peter Kirby et al.
Hyperdimensional computing (HDC) is gaining popularity as a lightweight alternative computing paradigm, where data are represented as long vectors (commonly of dimension 10,000) and processed using simple algebraic operations. In the two-pa...
Shape Matters: Few-Shot Object Classification From High-Information Contour Features [0.03%]
形必有因：基于高信息轮廓特征的Few-shot物体分类
Maria Osório,Alexandre Bernardino,Andreas Wichert
Maria Osório
A key challenge in visual object recognition is developing models that generalize from limited data while maintaining transparency in their decision making. We propose a biologically inspired model that addresses both issues by classifying ...
Joshua Hess,Quaid Morris
Joshua Hess
This letter shows that generative diffusion processes converge to associative memory systems at vanishing noise levels and characterizes the stability, robustness, memorization, and generation dynamics of both model classes. Morse-Smale dyn...
Neuronal Spike Trains as Functional-Analytic Distributions: Representation, Analysis, and Significance [0.03%]
神经脉冲序列的功能分析分布表示、分析及其意义
Gabriel A Silva
Gabriel A Silva
The action potential constitutes the digital component of the signaling dynamics of neurons. But the biophysical nature of the full-time course of the action potential associated with changes in membrane potential is mathematically distinct...
Quantifying Information Stored in Synaptic Connections Rather Than in Firing Activities of Neural Networks [0.03%]
量化存储在突触连接中的信息而非神经网络放电活动中的信息
Xinhao Fan,Shreesh P Mysore
Xinhao Fan
A cornerstone of our understanding of both biological and artificial neural networks is that they store information in the strengths of synaptic connections among the neurons. However, in contrast to the well-established theory for quantify...
Unsupervised Feature Selection Using Bayesian Tucker Decomposition [0.03%]
基于贝叶斯Tucker分解的无监督特征选择方法研究
Y-H Taguchi,Yoh-Ichi Mototake
Y-H Taguchi
In this letter, we propose Bayesian Tucker decomposition (BTuD) in which the residuals are supposed to follow. Although we have proposed an algorithm to perform the proposed BTuD, the conventional higher-order orthogonal iteration can gener...