Showing results 4391-4400 of >4,480 (page 440)
https://towardsdatascience.com/neural-networks-are-fundamentally-bayesian-bee9a172fad8/

Stochastic Gradient Descent approximates Bayesian sampling

https://arxiv.org/abs/1707.01429

Abstract page for arXiv paper 1707.01429: Theory of the superposition principle for randomized connectionist representations in neural networks

https://phys.org/news/2019-03-neural-networks-crowd-emotions.html

Scholars from the Higher School Of Economics have developed an algorithm that detects emotions in a group of people on a low-quality video. The solution provides a final decision in just one hundredth of a second, which is faster than any other existing algorithms with similar accuracy. The results have been described in the paper 'Emotion Recognition of a Group of People in Video Analytics Using Deep Off-the-Shelf Image Embeddings.'

https://foldoc.org/artificial+neural+network

neural network ⇝ artificial neural network < artificial intelligence > (ANN, commonly just "neural network" or "neural net") A network of many very simple processors ("units" or "neurons"), each possibly having a (small amount of) local memory. The units are connected by unidirectional communication channels ("connections"), which carry numeric (as opposed to symbolic) data. The units operate only on their local data and on the inputs they receive via the connections. A neural network is a processing

https://www.educba.com/neural-network-algorithms/

Guide to Neural Network Algorithms. Here we discuss the overview of Neural Network Algorithm with four different algorithms respectively

https://www.emergentmind.com/papers/1808.00508

This paper introduces the Neural Arithmetic Logic Unit (NALU), a module that enables neural networks to systematically generalize arithmetic operations beyond trained numeric ranges

https://www.exxactcorp.com/blog/Deep-Learning/a-friendly-introduction-to-graph-neural-networks

Exxact

https://paperswithcode.co/paper/2501.15925

Spiking Neural Networks (SNNs) are emerging as a brain-inspired alternative to traditional Artificial Neural Networks (ANNs), prized for their potential energy efficiency

https://www.quarkml.com/2023/08/recurrent-neural-networks-explained.html

You often heard about AI learning to trade, predicting stock prices, recognizing speech, translating language, and even generating human-level text from scratch in a modern scenario. All the advancements in these areas started from the idea of sequence modeling . Sequence modeling is a method of…

https://link.springer.com/article/10.1186/1471-2156-10-87

Our aim is to investigate the ability of neural networks to model different two-locus disease models. We conduct a simulation study to compare neural netwo

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