https://logb-research.github.io/blog/2024/ckn Kernel Trick I – Deep Convolutional Representations in RKHSOussama Zekri, Ambroise OdonnatJuly 18, 2024 “…we focus on the Convolutional Kernel Network (CKN) architecture proposed in End-to-End Kernel Learning with
What I Read: Convolutions, Probability
https://www.countbayesie.com/blog/2022/11/30/understanding-convolutions-in-probability-a-mad-science-perspective Understanding Convolutions in Probability: A Mad-Science PerspectiveWill Kurt, Count BayesieDecember 01, 2022 “If you’ve ever done much mad science you’ll know that a major problem is selectively determining the
What I Read: Beyond Message Passing, Graph Neural Networks
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What I Read: Understanding Convolutions on Graphs
https://distill.pub/2021/understanding-gnns/ Understanding Convolutions on GraphsUnderstanding the building blocks and design choices of graph neural networks.Ameya DaigavaneBalaraman RavindranGaurav AggarwalGoogle ResearchSept. 2, 202110.23915/distill.00032 “Graph neural networks (GNNs) are a family of neural