[1] A Gentle Introduction to Graph Neural Networks
[2] Graph neural networks: A review of methods and applications
...大约 8 分钟
交通仿真
基于元胞自动机(Cellular Automata,CA),模拟交通流、行人流过程。
交通规划原理
四种增长系数法预测交通分布的GUI编写
路径规划
改进A*、Dijkstra、Floyd、0-1规划模型实现全局路径规划
机器学习
机器学习一些常见代码（BP、Pytorch实现ANN、MNIST手写数字识别等）
数学建模
常见数学建模算法整理
个人简介
谈谈自己
This article will introduce a powerful technique in machine learning called Ateention Mechanism.
The core method of attention mechanism is to pay more attention to what we want. It allows model to weigh the importance of different parts of input dynamically rather than treating them equally. The model learns to assign higher weights to the most relevant elements.
...大约 6 分钟
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Introduction to Control Variate
Target
Reduce the variance of a random variable .
...大约 1 分钟
This paper is published at 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024. Full paper at
Abstract
Abstract — When coordinating the motion of connected autonomous vehicles at a signal-free intersection, the vehicles from each direction naturally forms a team and each team seeks to minimize their own traversal time through the intersection, without concerning the traversal times of other teams. Since the intersection is shared by all teams and agent-agent collision must be avoided, the coordination has to trade the traversal time of one team for the other. This paper thus investigates a problem called Multi-Agent Teamwise Cooperative Path Finding (TCPF), which seeks a set of collision-free paths for the agents from their respective start to goal locations, and agents are grouped into multiple teams with each team having its own objective function to optimize. In general, there are more than one teams and hence multiple objectives. TCPF thus seeks the Pareto-optimal front that represents possible tradeoffs among the teams. We develop a centralized planner for TCPF by leveraging the Multi-Agent Path Finding techniques to resolve agent-agent collision, and Multi-Objective Optimization to find Pareto-optimal solutions. We analyze the completeness and optimality of the planner, which is then tested in various settings with up to 40 agents to verify the runtime efficiency and showcase the usage in intersection coordination.
...大约 8 分钟
拨片
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拿的位置：拨片一般捏在1/2或2/3处，不要捏的太紧，靠手指指纹与拨片表面摩擦力来固定。
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拨弦位置：拨片1-2mm与琴弦接触。
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角度：拨片与琴弦角度如下图：
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五线谱
五线谱主要是四个内容：什么调，什么节奏，不同位置音符代表不同音高（由下图，从下往上依次是MI FA SOL LA SI DO RE MI FA），以及音符不同时值带来的节奏。
两线时间叫做间。
...小于 1 分钟
节奏是用音强弱组织起来的音的长短关系，强调长短，合拍。
节奏型是曲中典型的、反复出现的节奏片段。
节拍是强拍和弱拍按照一定顺序的循环，强调强弱。节拍的节是循环的节点，即小节，图中表示为竖线，后面跟一个强拍。
常说的四四拍：
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This paper presents a network-based approach to solving the Min-Max Multiple Traveling Salesman Problem (MTSP) by integrating a deep learning model with a traditional TSP solver. The MTSP problem is formulated as a bilevel optimization problem:
...大约 1 分钟