Showing results 6211-6220 of >6,301 (page 622)
https://digiday.com/marketing/wtf-neuro-decision-making/

# Explainer: How neural networks are changing credit scores By Digiday • February 27, 2017 • A credit score has a major impact on a person’s life. It’s the key to getting a car loan, a house or an apartment. The traditional way scores are calculated is a method called logistic regression, which means assigning a value to a number of factors in your financial life (for example, payment history, number of credit accounts, length of credit history) and weighing them. But credit bureaus are now looking

https://link.springer.com/chapter/10.1007/978-3-031-34214-1_10

Neural Networks (NNs) are used in various application areas to identify objects. Reliable behavior of NNs is an important aspect, especially for embedded systems. In this paper, we focus on the analysis of NNs to find correlations between their characteristics in

https://leemeng.tw/regularization-for-multi-layer-neural-networks-in-tensorflow.html

The goal of this assignment is to explore regularization techniques.

https://proceedings.mlr.press/v56/Choi16.html

Doctor AI: Predicting Clinical Events via Recurrent Neural NetworksEdward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart

https://www.aiweirdness.com/aw-yeah-its-time-for-cookies-with-18-12-07/

So there’s these computer programs called artificial neural networks that are good at imitating things. By seeing examples of what humans did, they can learn to translate languages, predict product sales, and even categorize text and images as innocuous or explicit (it has a lot of trouble with this last task, as it turns out

https://techxplore.com/news/2022-06-neuromorphic-architecture-deep-neural-networks.html

As artificial intelligence and deep learning techniques become increasingly advanced, engineers will need to create hardware that can run their computations both reliably and efficiently. Neuromorphic computing hardware, ...

https://www.docswell.com/s/DeepLearning2023/KM1Y36-dlpervasive-attention-2d-convolutional-neural-networks-for-sequencetosequence-prediction

ドクセルはスライドやPDFをかんたんに共有できるサイトです

https://www.emergentmind.com/papers/2402.04710

Graph Neural Networks (GNNs) have gained considerable traction for their capability to effectively process topological data, yet their interpretability remains a critical concern. Current interpretation methods are dominated by post-hoc explanations to provide a transparent and intuitive understanding of GNNs. However, they have limited performance in interpreting complicated subgraphs and can't utilize the explanation to advance GNN predictions. On the other hand, transparent GNN models are proposed to cap

https://research.atspotify.com/publications/personalized-audiobook-recommendations-at-spotify-through-graph-neural-networks

Spotify’s official technology blog

https://hasgeek.com/fpindia/bangalore-fp-october-2025-meetup/sub/functional-programming-in-lisp-and-neural-networks-H58XY9KgxWv5ErZM5Pxpps

Lisp was one of the first high-level programming languages. And, in its conception, it was the language associated with “AI” systems. But this AI, in its pri…

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