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J. Solomon, F. de Goes, G. Peyré, M. Cuturi, A. Butscher, A. Nguyen, T. Du, L. Guibas. Convolutional Wasserstein Distances: Efficient Optimal Transportation on Geometric Domains. ACM Transactions on Graphics (Proc. SIGGRAPH 2015), 34(4), pp. 66:1–66:11, 2015
35岁程序员退路之量化投资学习笔记
Adversarial Training Methods for Network Embedding, WWW2019.
互联网黑话词汇表,包含“赋能、抓手、闭环、沉淀、打通”等阿里味儿词汇
Compute arboricity and forest decomposition of graphs.
Using a paper from Google DeepMind I've developed a new version of the DQN using threads exploration instead of memory replay as explain in here: http://arxiv.org/pdf/1602.01783v1.pdf I used the one-step-Q-learning pseudocode, and now we can train the Pong game in less than 20 hours and without any GPU or network distribution.
Paper Lists for Graph Neural Networks
A proximal bundle method for minimizing a sum of functions. Proximal steps for subfunctions are computed with a multi plane block coordinate Frank-Wolfe method.
Code of paper "Joint Link Prediction and Network Alignment via Cross-graph Embedding"
Official Matplotlib cheat sheets
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
A python script for detecting communities in graphs using the clique percolation method.
📚 Solutions to Introduction to Algorithms Third Edition
Network alignment using proximity-preserving node embedding and subspace alignment
ConicBundle software from https://www-user.tu-chemnitz.de/~helmberg/ConicBundle/ with additional cmake script
COT-GAN: Generating Sequential Data via Causal Optimal Transport
Sorting algorithms & related tools for C++14
blog
Construct integer linear problems pragmatically from dual decomposition based formulations. Solve them with various backends, like ILP solvers or SAT-based ones.
Implementation of Deep Graph Matching Consensus in PyTorch
DeepWalk - Deep Learning for Graphs
[KDD 2021, Research Track] DiffMG: Differentiable Meta Graph Search for Heterogeneous Graph Neural Networks
Efficient Diffusion for Image Retrieval
Codes for calculating graph Diffusion Distance Efficiently.
Mixing Integer Linear Programming and Deep Graph Matching
Codes for WWW'19 Paper-DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data
An implementation of the Functional Map framework for finding correspondences between Meshes, Images or Graphs.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.