Graph Theory Blinks (Fall 2019)
37 videos • 24,692 views • by BASIRA Lab
1
Graph Theory Blink 1.1 (Introduction to Graph Theory)
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2
Graph Theory Blink 1.2 (Graphs are everywhere: from bees to brains)
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3
Graph Theory Blink 1.3 (Graph representation and adjacency matrix)
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4
Graph Theory Blink 1.4 (Graph types: simple, complete, subgraph, hypergraph, annotated graphs)
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5
Graph Theory Blink 1.5 (Introduction to graph topology: node degree and SNAP library)
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6
Graph Theory Blink 2.1 (Introduction to node centrality in graphs —degree centrality)
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7
Graph Theory Blink 2.2 (degree centrality and eigenvector centrality)
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8
Graph Theory Blink 2.3 (Eigen decomposition of covariance and adjacency matrices)
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9
Graph Theory Blink 2.4 (Eigenvector centrality and PageRank centrality)
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10
Graph Theory Blink 2.5 (Closeness centrality)
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11
Graph Theory Blink 2.6 (Betweenness centrality and delta centrality)
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12
Graph Theory Blink 3.1 (Connected components in a graph and minimum spanning tree)
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13
Graph Theory Blink 3.2 (Connected components in directed and undirected graphs)
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14
Graph Theory Blink 3.3 (Graph percolation, perturbation and robustness)
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15
Graph Theory Blink 4.1 (Core-periphery graph organization)
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16
Graph Theory Blink 4.2 (k-core and s-core graph decomposition)
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17
Graph Theory Blink 4.3 (Graph rich clubs and rich-club coefficient)
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18
Graph Theory Blink 5.1 (Shortest path routing, diffusion and navigation)
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19
Graph Theory Blink 5.2 (Walks, trails, paths, and cycles in graphs)
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20
Graph Theory 5.3 (Similarity-to-distance remapping in weighted graphs)
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21
Graph Theory Blink 5.4 (Shortest path length computation by Dijkstra's algorithm)
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22
Graph Theory Blink 5.5 (Graph efficiency measures)
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23
Graph Theory 6.1 (Comparing shortest path routing and diffusion on graphs)
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24
Graph Theory Blink 6.2 (Search information using random walk on graph)
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25
Graph Theory Blink 6.3 (Path transitivity of random walker on graphs)
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26
Graph Theory Blink 6.4 (Shortest path probability of a random walker and graph Laplacian)
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27
Graph Theory Blink 6.5 (Mean first passage of a random walker on a graph)
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28
Graph Theory Blink 6.6 (Graph diffusion efficiency and communicability)
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29
Graph Theory Blink 7.1 (Graph Self-Diffusion for Image Segmentation Wang et al , CVPR 2012)
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30
Graph Theory Blink 8.1 (How to fuse or merge graphs?)
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31
Graph Theory Blink 8.2 (Graph cross-diffusion and fusion)
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32
Graph Theory Blink 9.1 (Graph Modularity and Hierarchical Modularity)
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33
Graph Theory Blink 9.2 (Benefits of hierarchical modularity and clustering for module detection)
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34
Graph Theory Blink 10 (3 rules of geometric deep learning: locality, aggregation, and composition).
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35
Best Project Presentation on Lanczosnet (multi-scale deep graph convolutional networks #ICLR2019)
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36
Project Presentation on Learning Structural Node Embeddings via Diffusion Wavelets (ACM, 2018)
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37
Best Graph Theory Project | Ant Social Organization
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