Deep learning,Implicit discourse relation classification,Word embedding,Neural networkThe neural components in deep learning framework are crucial for the performance of many natural language processing tasks.So far there is no systematic work to investigate the influence of neural components on the ...
MIT researchers created a technique that can automatically describe the roles of individual neurons in a neural network with natural language. In this figure, the technique was able to identify “the top boundary of horizontal objects” in photographs, which are highlighted in whit...
The neural network architecture they developed, Netcast, involves storing weights in a central server that is connected to a novel piece of hardware called a smart transceiver. This smart transceiver, a thumb-sized chip that can receive and transmit data, uses technology known as silicon photonics...
HyperLib: Deep learning in the Hyperbolic space Background This library implements common Neural Network components in the hyperbolic space (using the Poincare model). The implementation of this library uses Tensorflow as a backend and can easily be used with Keras and is meant to help Data Scien...
论文名称:Interpreting and Disentangling Feature Components of Various Complexity from DNNs论文地址:[2006.15920] Interpreting and Disentangling Feature Components of Various Complexity from DNNs (arxiv.org) 1 Intro Deep neural network have demostrated significant success in various tasks. 除了DNNs的优越性能...
C++17 Autograd Neural Network FrameworkDemo: https://youtu.be/tH6AvNnQnLQ A flexible and extensible framework in pure C++17 designed to facilitate the construction, training, and evaluation of Neural Networks. Inspired by modern Deep Learning frameworks like PyTorch and TensorFlow, this project prov...
Currently, welding quality detection remains dependent on manual operation, while the increase in the span and intricacy of steel bridges has rendered the
TensorFlow is one of the most in-demand tools used by ML or AI engineers. It is an open-source framework, developed by Google, that is used to build various machine learning and deep learning models. TensorFlow helps you to train and execute neural network image recognition, natural language...
For example, autoencoders are a neural network architecture currently used to infer a latent representation of the mRNA transcription patterns obtained from both bulk and single-cell samples27,28. This representation can be used as a regulatory barcode to generate gene function prediction scores withi...
CUDA Deep Neural Network (cuDNN) cuDNN is an NVIDIA library used by deep learning frameworks to accelerate common components, such as pooling, normalization, and backward convolution. Jetpack 5.0 comes with cuDNN 8.3.2, including bugfixes and new enhancements. TensorRT TensorRT is a framework...