Blog Topics Advertise Join Newsletter Can graph machine learning identify hate speech in online social networks? Online hate speech is a complex subject. Follow this demonstration using state-of-the-art graph neural network models to detect hateful users based on their activities on the Twitter social network. --> comments By Pantelis Elinas, Anna Leontjeva, and Yuriy Tyshetskiy. Over three decades, the Internet has grown from a small network of computers used by research scientists to communicate and excha
The text discusses a method of exchanging data between programs without using DLLs, utilizing TXT files via RAM-Disk for high-speed communication. It highlights the advantages of this approach over DLLs, emphasizing simplicity and flexibility. The author also explores the use of neural networks for determining buy/sell signals in trading models, mentioning challenges related to dataset length and model variability
田中専務 拓海先生、最近薦められた論文の題名が難しくて頭が痛いんです。『Neural McKean-Vlaso
Why the batch-normalization layer is not used in the functional API model ?
My attempt at distilling the ideas behind the neural tangent kernel that is making waves in recent theoretical deep learning research
Backpropagation uses the chain rule to send the loss gradient backward through a network, computing weight gradients that gradient descent then uses.
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We’ve talked about neural nets before—the core machinery that makes deep learning so powerful. The Algorithm Artificial intelligence, demystified An award-winning research paper, explained 12.17.18 Hello Algorithm readers, If there’s one thing you learn from spending a week with AI researchers, it’s how much uncertainty exists in the field. We still don’t really know how neural networks work, how to improve their accuracy (besides just feeding them more data), or how to fix their biases. But bit
Skip to main content Frequency: Monthly ISSN: 1549-3636 (Print) ISSN: 1552-6607 (Online) Special Issues Research Article Open Access Identification of Influential Nodes With Topological Structure Via GRAPH Neural Network (GNN) Approach in Social Media Networks Rajnish Kumar1, Laxmi Ahuja2, Suman Mann3 and Sanmukh Kaur4 1 Department of Computer Science, Amity University Noida, India 2 Departmant of Information Technology, Amity University Noida, India 3 Department of Computer Science, Panipat Institute of En
A recent paper in Neuron from Kanaka Rajan, Chris Harvey and David Tank sets out to demonstrate how relatively unstructured networks can give rise to highly structured outputs that persist on slow timescales relevant to behaviors like decision-making and working memory. Such unstructured networks seem at first like exactly the wrong thing to support stimulus-driven persistent activity