the dependence of a network’s structure on its past, is currently a matter of debate. Here we show that the memory of a temporal network is inherently multidimensional, and we introduce a mathematical framework for defining and efficiently estimating the microscopic shape of memory, which ...
研究领域:网络科学,时序网络,记忆形状,虚拟循环 徐恩峤| 作者 邓一雪| 编辑 论文题目: The shape of memory in temporal networks 论文地址: 1. 标量网络记忆难以洞察相关链接动力学 网络记忆(network memory),即某个网络在何种程度上与其历史相关,是时序网络动力学研究的重要内容。传统的标量网络记忆 Ω(G) 是...
By transforming narratives into networks of events, we demonstrate that more central events—those with stronger semantic or causal connections to other events—are better remembered. During encoding, central events evoke larger hippocampal event boundary responses associated with memory formation. During ...
Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks Anomaly Detection Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection Boosting Graph Anomaly Detection with Adaptive Message Passing LLM Talk like a Graph: Encoding Graphs for Large Language Models Lab...
Reading Relevant Feature from Global Representation Memory for Visual Object Tracking, Xinyu Zhou, Pinxue Guo, Lingyi Hong, Jinglun Li, Wei Zhang, Weifeng Ge, Wenqiang Zhang [Paper] AAAI-2024 ODTrack: Online Dense Temporal Token Learning for Visual Tracking, Yaozong Zheng; Bineng Zhong; Qihua ...
Indeed, shelter volume quantification is feasible, especially with automated computation with a simple function in R code and could be used to estimate the shelter capacity of reefscapes in spatial and temporal surveys. Further analyses are needed to evaluate the 2D-3D relationships for other coral...
In this paper, the newly proposed CoCosNet v2 establishes full-resolution correspondence for cross-domain images. Researchers proposed two techniques to improve the memory efficiency of high-resolution correspondence. First, they adopted a coarse-to-fine strategy ...
the outputs of theteacher can vary dramatically on the same instance during different trainingstages, introducing unexpected noise and leading to catastrophic forgettingcaused by inconsistent objectives. In this paper, we first integrate instancetemporal consistency into current instance discrimination paradigms...
Human emotions fluctuate over time. However, it is unclear how these shifting emotional states influence the organization of episodic memory. Here, we examine how emotion dynamics transform experiences into memorable events. Using custom musical pieces a
such methods generally rely on training big models of neural networks posing severe limitations on their deployment in the most common applications8. In fact, there is a growing demand for developing small, lightweight models that are capable of fast inference and also fast adaptation - inspired ...