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Fresh picks from ArXiv
ICML 20 submissions, AISTATS 20, graphs in math, and Stephen Hawking 👨‍🔬

ICML 2020 submissions
Fast Detection of Maximum Common Subgraph via Deep Q-Learning (https://arxiv.org/abs/2002.03129)
Random Features Strengthen Graph Neural Networks (https://arxiv.org/abs/2002.03155)
Hierarchical Generation of Molecular Graphs using Structural Motifs (https://arxiv.org/pdf/2002.03230.pdf)
Graph Neural Distance Metric Learning with Graph-Bert (https://arxiv.org/abs/2002.03427)
Segmented Graph-Bert for Graph Instance Modeling (https://arxiv.org/abs/2002.03283)
Haar Graph Pooling (https://arxiv.org/abs/1909.11580)
Constant Time Graph Neural Networks (https://arxiv.org/abs/1901.07868)
@Machine_learn
AISTATS 20
Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis (https://arxiv.org/abs/1907.05632)
@Machine_learn
Math
Some arithmetical problems that are obtained by analyzing proofs and infinite graphs (https://arxiv.org/abs/2002.03075)
Extra pearls in graph theory (https://arxiv.org/abs/1812.06627)
Distance Metric Learning for Graph Structured Data (https://arxiv.org/abs/2002.00727)
@Machine_learn
Surveys
Generalized metric spaces. Relations with graphs, ordered sets and automata : A survey (https://arxiv.org/abs/2002.03019)
@Machine_learn
Stephen Hawking 👨‍🔬
Stephen William Hawking: A Biographical Memoir (https://arxiv.org/abs/2002.03185)



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@Machine_learn

Fresh picks from ArXiv
ICML 20 submissions, AISTATS 20, graphs in math, and Stephen Hawking 👨‍🔬

ICML 2020 submissions
Fast Detection of Maximum Common Subgraph via Deep Q-Learning (https://arxiv.org/abs/2002.03129)
Random Features Strengthen Graph Neural Networks (https://arxiv.org/abs/2002.03155)
Hierarchical Generation of Molecular Graphs using Structural Motifs (https://arxiv.org/pdf/2002.03230.pdf)
Graph Neural Distance Metric Learning with Graph-Bert (https://arxiv.org/abs/2002.03427)
Segmented Graph-Bert for Graph Instance Modeling (https://arxiv.org/abs/2002.03283)
Haar Graph Pooling (https://arxiv.org/abs/1909.11580)
Constant Time Graph Neural Networks (https://arxiv.org/abs/1901.07868)
@Machine_learn
AISTATS 20
Laplacian-Regularized Graph Bandits: Algorithms and Theoretical Analysis (https://arxiv.org/abs/1907.05632)
@Machine_learn
Math
Some arithmetical problems that are obtained by analyzing proofs and infinite graphs (https://arxiv.org/abs/2002.03075)
Extra pearls in graph theory (https://arxiv.org/abs/1812.06627)
Distance Metric Learning for Graph Structured Data (https://arxiv.org/abs/2002.00727)
@Machine_learn
Surveys
Generalized metric spaces. Relations with graphs, ordered sets and automata : A survey (https://arxiv.org/abs/2002.03019)
@Machine_learn
Stephen Hawking 👨‍🔬
Stephen William Hawking: A Biographical Memoir (https://arxiv.org/abs/2002.03185)

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Telegram Be The Next Best SPAC

I have no inside knowledge of a potential stock listing of the popular anti-Whatsapp messaging app, Telegram. But I know this much, judging by most people I talk to, especially crypto investors, if Telegram ever went public, people would gobble it up. I know I would. I’m waiting for it. So is Sergei Sergienko, who claims he owns $800,000 of Telegram’s pre-initial coin offering (ICO) tokens. “If Telegram does a SPAC IPO, there would be demand for this issue. It would probably outstrip the interest we saw during the ICO. Why? Because as of right now Telegram looks like a liberal application that can accept anyone - right after WhatsApp and others have turn on the censorship,” he says.

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