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2022_recommend
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MIT Shape Analysis
https://www.youtube.com/watch?v=VjyBp6PrvB4&list=PLQ3UicqQtfNtUcdTMLgKSTTOiEsCw2VBW
https://groups.csail.mit.edu/gdpgroup/assets/6838_spring_2021/1_introduction.pdf
Pattern Recognition and Machine Learning
Mathematics in Deep learning
Book:Deep Generative model by Jakub, a intro book about DGL, user-friendly，这个比较简单
Review: Deep Geometric Learning, 这个比较难，还涉及到信号处理以及NLP的知识，建议后期观看
Toturial:pytorch geometric tutorial, Pyg的入门版本，youtube配有视频，而且附有代码。https://antoniolonga.github.io/Pytorch_geometric_tutorials/
Toturial:E3NN的toturial，关于equvirance, invariance以及group theory的东西。这个涉及地非常物理，推荐国内的书为北大物院李新征群论的讲义和凝聚态物理当中的群论，国外的书一搜一大把
这个是MSR的2021年Seminar https://e3nn.org/e3nn-tutorial-mrs-fall-2021/
人工智能的矩阵代数方法
人工智能的数学基础知识可以分为高等数学、线性代数、概率论与数理统计三部分
推荐Stanford CS229, 相关的Github网址https://github.com/fengdu78/Data-Science-Notes/tree/master/0.math
然后各个部分其实就是吴恩达或者是李宏毅的课程，一抓一大把
DNN 无法很好地拟合高频函数：https://zhuanlan.zhihu.com/p/396920175
图神经相关：
Stanford CS224W 图机器学习
3D图像：
优化问题：
Graph Matching
Shape Matching
Computer Graphics
https://www.youtube.com/playlist?list=PL9_jI1bdZmz2emSh0UQ5iOdT2xRHFHL7E
Mesh Generation and Geometry Processing in Graphics, Engineering, and Modeling
https://people.eecs.berkeley.edu/~jrs/mesh/
geodesic distance of graphs - blog
https://kadircenk.com/blog/process-the-mesh-part-1-geodesic-distance-farthest-point-sampling-agd-and-mgd-local-maximas/#:~:text=When%20we%20represent%20the%20surface,Path%20algorithm%20on%20the%20graph.
大部分机器学习
http://blog.showmeai.tech/cmu-15-462/
bro, 你肯定想学一些几何的东西吧，这里是讲旋转矩阵的博主https://zhuanlan.zhihu.com/p/445936075
下面这个链接做的很好，百度给出的傻逼东西都是废话，根本算不了，下面的这个链接讨论了经典力学的变分方法以及各种良好的概念。
md果然要补理论力学......
https://phys.libretexts.org/Bookshelves/Classical_Mechanics/Variational_Principles_in_Classical_Mechanics_(Cline)/13%3A_Rigid-body_Rotation/13.03%3A_Rigid-body_Rotation_about_a_Body-Fixed_Point
机器人学
https://www.bilibili.com/video/BV1v4411H7ez?spm_id_from=333.337.search-card.all.click
台湾大学的机器人学
Stanford的机器人学，学习机器人控制算法
Lie group and Lie algebra也跑不掉，学无止境
矢量分析
【西电/梁昌洪】场论与复变函数 -- good bro
书《物理学中的张量分析》
Spacetime and geometry
Stochastic models, information theory, and Lie groups, volume 2: Analytic methods and modern applications
schrodinger_bridge
https://jtt94.github.io/papers/schrodinger_bridge
CS&SS/STAT 564: Bayesian Statistics for the Social Sciences.
https://www.bilibili.com/video/BV1Wp4y1v7mt?spm_id_from=333.337.search-card.all.click
coursera上的一门新课，UCSC开设，主要讲机器学习里面的混合模型，以及贝叶斯混合模型。练习课画质略渣，有条件建议直接上coursera
https://www.bilibili.com/video/BV1iV411v7Yw?p=39
https://developer.aliyun.com/article/838115
cs228Learning in undirected models
https://github.com/wiseodd/MCMC
https://www.bilibili.com/video/BV1rZ4y1X74i?spm_id_from=333.337.search-card.all.click
分子对接
https://chem-workflows.com/articles/2021/09/18/1-molecular-docking/
https://bioinformaticsreview.com/20200716/prepare-receptor-and-ligand-files-for-docking-using-python-scripts/
PDBProcessor
https://github.com/openmm/pdbfixer
rdkit各种问题
https://greglandrum.github.io/rdkit-blog/prototypes/technical/2020/01/25/trying-the-tautomer-canonicalization-code.html
Geometry in Robotics
https://faculty.sites.iastate.edu/jia/foundations-robotics-and-computer-vision-com-s-477577