All About Neural Net 系列:All About Neural Net 这篇文章主要介绍大名鼎鼎的残差结构,也就是著名的CVPR 2016 best paper Deep Residual Learning for Image Recognitionwww.cv-foundation.org/openaccess/content_cvpr_2016/papers/He_Deep_Residual_Learning_CVPR_2016_paper.pdf 以及残差结构的改进探索,发表在...
All About Neural Net 系列:All About Neural Net这篇文章介绍分别发表在CVPR 2018和CVPR 2019论文 Squeeze-and-Excitation NetworksSelective Kernel NetworksSqueeze-and-Excitation Network (SENet) 和 Select…
Highway Network与ResNet具有相似性，两者的结构都包含两个分支进行合并。论文中transform gate的定义为g(x;θ)=sigmoid(wx+b)，其中w和b为权重和偏置。门控机制不仅适用于Highway Network，也可应用于其他场景。ICML 2017上的论文《Language Modeling with Gated Convolutional Networks》提出了一种Gated ...
Dubrawski from N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting From the picture above, we notice that the model is very similar to N-BEATS: the model makes both a forecast and backcast, it is made of stacks and blocks, the final prediction is the sum of the ...
Neural Networks Neural Networks Articles & Issues About Publish Order journal Guide for authors All issues 2025 — Volumes 181-185 Volume 185 In progress(May 2025) Volume 184 In progress(April 2025) Volume 183 March 2025 Volume 182 February 2025...
Initialization Parameter Sweep in ATHENA: Optimizing Neural Networks for Detecting Gene-Gene Interactions in the Presence of Small Main Effects. Recent advances in genotyping technology have led to the generation of an enormous quantity of genetic data. Traditional methods of statistical analysis ha......
This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL).oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning ...
⭐ WeightWatcher - WeightWatcher tool for predicting the accuracy of Deep Neural Networks [GitHub, 1453 stars] Data and Model Observability General ⭐ Arize AI - embedding drift monitoring for NLP models ⭐ Arize-Phoenix - ML observability for LLMs, vision, language, and tabular models ⭐...
Neural networks and other artificial intelligence programs require an initial set of data, called a training dataset, to act as a baseline for further application and utilization. This dataset is the foundation for the program's growing library of information. The training dataset must be accurately...
We exploit wavelength division multiplexing techniques to implement a scalable circuit architecture for photonic neural networks, successfully demonstrating pattern recognition directly in the optical domain. Such photonic neurosynaptic networks promise access to the high speed and high bandwidth inherent to ...