Kimon Fountoulakis (@kfountou)
자신의 마지막 GNN 논문일 수 있다고 밝히며 'Learning to Execute Graph Algorithms Exactly with Graph Neural Networks'를 소개함. @PetarV_93가 대중화한 neural algorithmic reasoning 맥락에서, GNN이 그래프 알고리즘을 정확히 실행할 수 있는지에 대한 연구 주제임을 언급함.
Kimon Fountoulakis (@kfountou)
자신의 마지막 GNN 논문일 수 있다고 밝히며 'Learning to Execute Graph Algorithms Exactly with Graph Neural Networks'를 소개함. @PetarV_93가 대중화한 neural algorithmic reasoning 맥락에서, GNN이 그래프 알고리즘을 정확히 실행할 수 있는지에 대한 연구 주제임을 언급함.
This somehow sounds too good to be true: "Attractors Is All You Need: Parity Games In Polynomial Time" (https://arxiv.org/abs/2511.03752)
I had a quick look, but I don't remember the typical strategies of algorithms for parity games anymore. Any opinions?
Iterative DFS with stack-based graph traversal (2024)
https://dwf.dev/blog/2024/09/23/2024/dfs-iterative-stack-based
#HackerNews #IterativeDFS #StackTraversal #GraphAlgorithms #DepthFirstSearch #2024Trends
Trying to tame the NP-complete beast — writing a paper about my algorithm for solving the Hamiltonian cycle #graphs #hamiltoncycle #npcomplete #graphalgorithms #computerscience #heuristics #optimization #research #computationalcomplexity #hacking #latex
Efficiently Creating and Visualizing Symmetric Adjacency Matrices in Python
Master Python Adjacency Matrix techniques! Learn efficient creation, NetworkX visualization, & handling of large datasets. Represent & analyze complex relationships in your data. #PythonAdjacencyMatrix #GraphTheory #NetworkX #DataVisualization #DataScience #GraphAlgorithms
https://tech-champion.com/programming/python-programming/efficiently-creating-and-visualizing-symmetric-adjacency-matrices-in-python/
Q: Who is Edsger W. Dijkstra? A: goto: . #LinkedData #SmartData #GraphAlgorithms :
The Role of Graph Algorithms in Drug Discovery for Cardiovascular Disease
Drug discovery is a time-consuming and costly process, especially for cardiovascular diseases (CVD). Graph algorithms are revolutionizing this space by mapping complex interactions between biological systems and drug compounds. This helps researchers identify promising drug candidates faster, reducing time-to-market and enabling personalized treatment strategies.