Скачать с ютуб #71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED] в хорошем качестве

#71 - ZAK JOST (Graph Neural Networks + Geometric DL) [UNPLUGGED]

Special discount link for Zak's GNN course - https://bit.ly/3uqmYVq Patreon:   / mlst   Discord:   / discord   Pod: https://anchor.fm/machinelearningstre... Want to sponsor MLST!? Let us know on Linkedin / Twitter. [00:00:00] Preamble [00:03:12] Geometric deep learning [00:10:04] Message passing [00:20:42] Top down vs bottom up [00:24:59] All NN architectures are different forms of information diffusion processes (squashing and smoothing problem) [00:29:51] Graph rewiring [00:31:38] Back to information diffusion [00:42:43] Transformers vs GNNs [00:47:10] Equivariant subgraph aggregation networks + WL test [00:55:36] Do equivariant layers aggregate too? [00:57:49] Zak's GNN course References; Welcome AI Overlords YT channel    / @welcomeaioverlords   Author Interview - Equivariant Subgraph Aggregation Networks    • Author Interview - Equivariant Subgra...   https://arxiv.org/abs/2110.02910 Geometric Deep Learning Grids, Groups, Graphs, Geodesics, and Gauges https://arxiv.org/abs/2104.13478 Joan Bruna sources of error in learning https://cims.nyu.edu/~bruna/    • AMMI Course "Geometric Deep Learning"...   Blind men and an elephant https://en.wikipedia.org/wiki/Blind_m... Geometric Deep Learning From Learning ODE Dynamics towards Graph Neural Diffusion [Brune] https://bathicmsworkshop.github.io/Ch... The Road to Reality: A Complete Guide to the Laws of the Universe https://www.amazon.co.uk/Road-Reality... Lenia - Mathematical Life Forms [Cellula Automata]    • Lenia - Mathematical Life Forms   Graph Neural Networks - a perspective from the ground up [Alex Foo]    • Graph Neural Networks - a perspective...   SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS [Kipf] https://arxiv.org/pdf/1609.02907.pdf Convolution theorem https://en.wikipedia.org/wiki/Convolu... https://en.wikipedia.org/wiki/Graph_F... Wavelets on Graphs via Spectral Graph Theory [Hammond] https://arxiv.org/pdf/0912.3848.pdf Growing Neural Cellular Automata https://distill.pub/2020/growing-ca/ Rediscovering the power of pairwise interactions [William Bialek] https://www.princeton.edu/~wbialek/ro... UNDERSTANDING OVER-SQUASHING AND BOTTLENECKS ON GRAPHS VIA CURVATURE [Topping12, inc Bronstein] https://arxiv.org/pdf/2111.14522.pdf https://towardsdatascience.com/over-s... GRAND: Graph Neural Diffusion [Chamberlain, inc Bronstein] http://proceedings.mlr.press/v139/cha...   / graph-neural-networks-as-neural-diffusion-...   Dr. Daniele Grattarola https://danielegrattarola.github.io/ ON THE UNREASONABLE EFFECTIVENESS OF FEATURE PROPAGATION IN LEARNING ON GRAPHS WITH MISSING NODE FEATURES [Rossi + Bronstein et al] https://arxiv.org/pdf/2111.12128.pdf A Spline Theory of Deep Learning [_**Balestriero**_] https://proceedings.mlr.press/v80/bal... COMBINING LABEL PROPAGATION AND SIMPLE MODELS OUT-PERFORMS GRAPH NEURAL NETWORK (Correct and smooth) [Huang] https://arxiv.org/pdf/2010.13993.pdf Review: Deep Learning on Sets [Fuchs] https://fabianfuchsml.github.io/learn... Transformers are Graph Neural Networks https://thegradient.pub/transformers-... The Weisfeiler-Lehman Isomorphism Test https://davidbieber.com/post/2019-05-... How Powerful are Graph Neural Networks? [Xu, Stefanie Jegelka] https://arxiv.org/abs/1810.00826