Resources
Useful links for research, Graph Neural Networks, Software Engineering research, and so on.
Table of Contents
Quotes
"Don't pray for fair weather, pray for courage" - Mau Piailug (1932-2010) master non-instrument open-ocean navigator
“Science is built up with facts, as a house is with stones. But a collection of facts is no more a science than a heap of stones is a house” - Henri Poincare
Useful Links (2024)
Useful Links (2023)
Useful Links (2022)
Awesome Knowledge Management: A curated list of amazingly awesome articles, people, applications, software libraries and projects related to the knowledge management space.
Graph signal processing for machine learning [Slides1] [Slides2] [Slides3]
IEEE ICASSP Tutorial, Toronto, ON, Canada, June 2021.
paper_writing_tips: Paper Writing Tips
awesome-phd-advice: Collection of advice for prospective and current Ph.D. students
the-art-of-command-line : Master the command line, in one page
Handout for the tutorial "Creating publication-quality figures with matplotlib"
Code snippets for custom style
Cowboy: An Agile Programming Methodology for a Solo Programmer
AI for Time Series (AI4TS) Papers, Tutorials, and Surveys
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.
A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.
IJCAI2022-Tutorial-Time-Series
IJCAI'22 Tutorial, Robust Time Series Analysis from Theory to Applications in the AI Era
Time-series Tutorial in KDD 2022
Github source for KDD'22 Time Series Tutorial website
Report your environment! python script from pyTorch
Statistical Comparisons of Classifiers over Multiple Data Sets (JMLR 2006)
I Am Iron Man: Leadership Lessons From Tony Stark written by John Rampton
Math behind GCN by Zhiping Xiao, 2018 [slide]
How to write a good paper by William T. Freeman [slide]
Multi-slice CT Image Reconstruction by Jiang Hsieh [slide]
CT Image Reconstruction by Terry Peters [slide]
Stanford EE369C: Medical Image Reconstruction [link]
Diffusion/SDE/ODE-based generative models papers (ICLR2023 Submitted)
Awesome-math: A curated list of awesome mathematics resources
Awesome-tips: various tips for researchers
How To Do A Good Literature Review | The PhD Voice Twitter
Graph Neural Networks: Foundations, Frontiers, and Applications
Geometric Deep Learning (Grids, Groups, Graphs, Geodesics, and Gauges)
Novelty in Science | Perceiving Systems Blog (perceiving-systems.blog)
Useful Links(2021)
How to get your paper accepted, written by Peter Pietzuch, Department of Computing Imperial College London
How to read a CS research paper, written by Philip W. L. Fong
Accelerate your research!
Connected Paper: this helps me to find easily the related work.
When you fell apart but got back up again
For a Good Talk!
Non-systematic Literature Review on Graphs (e.g. Awesome lists)
Graph Neural Networks
Graph-based Deep Learning Literature: links to conference publications in graph-based deep learning
GNNs and related works list: A list for GNNs and related works.
awesome deep gnn: Papers about developing deep Graph Neural Networks (GNNs)
Awesome Semi-Supervised Learning: An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
Awesome Community Detection Research Papers: A curated list of community detection research papers with implementations.
awesome-self-supervised-gnn: Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
Traffic Forecasting
GNN4Traffic: This is the repository for the collection of Graph Neural Network for Traffic Forecasting.
Traffic Prediction: A tabular summary of paper and publically available datasets.
Awesome Traffic Prediction: Useful resources for traffic prediction, including popular papers, datasets, tutorials, toolkits, and other helpful repositories.
Dynamic Graphs
Awesome-DynamicGraphLearning: Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs)
Further Reading
Graph at ICLR 2021: The core reading list for GNN researchers in ICLR 2021
Graph Adversarial Learning Literature: A curated list of adversarial attacks and defenses papers on graph-structured data.
SNAP Graph Workshop 2021: Stanford Graph Learning Online Workshop
Reading List of Papers about Homophily (Assortative) in GNNs
Non-systematic Literature Review (e.g. Awesome lists)
Recommender Systems
Awesome Recommender System: The collection of papers about the recommender system
Differential Equations
Tabular Data
Energy Based Models
Software Engineering
Awesome Software Engineering: A curated list of awesome software engineering resources.
Useful Links(2020)
The 3 Skills That Helped Me Become a Better Software Engineer
How to give a good research talk, Stephanie Weirich, University of Pennsylvania
How Not to Present a Paper, Anders Møller, Aarhus University