Networks, Neural network, Neuroscience, Artificial intelligence, Artificial neural network, Statistical classification
CUDA-X Accelerated DGL Containers for Large Graph Neural Networks
NVIDIA partnered with the DGL team to provide containers with the latest DGL, PyTorch, and SE(3)-Transformer for GPU-accelerated performance optimization.
CUDA-X Accelerated DGL Containers for Large Graph Neural Networks
NVIDIA partnered with the DGL team to provide containers with the latest DGL, PyTorch, and SE(3)-Transformer for GPU-accelerated performance optimization.
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Awesome-Pytorch-list
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc. - bharathgs/Awesome-pytorch-list
Now Available on Amazon SageMaker: The Deep Graph Library
Today, we’re happy to announce that the Deep Graph Library, an open source library built for easy implementation of graph neural networks, is now available on Amazon SageMaker. In recent ...
NVIDIA Launches New, Updated Accelerated Computing Libraries: NVIDIA ReOpt, cuQuantum, cuNumeric, cuGraph, Modulus, Morpheus, NeMo Megatron, Riva, RAPIDS, DOCA and Dozens More
65 software development kits for accelerating quantum computing, last-mile delivery, supercomputing for the PyData ecosystem and more enhance catalog of 150+ offerings.
How to Use Graph Neural Networks for Text Classification?
neural networks such as CNN can be applied to the regular grid structure which is helpful in working on arbitrarily structured graphs
5 Amazing Deep Learning Frameworks Every Data Scientist Must Know! (with Illustrated Infographic)
This article delves into 5 popular deep learning frameworks, their applications and how they compare against each other. A must-read for everyone!
Getting to Know Keras for New Data Scientists
This article was originally published on OpenDataScience.com, written by Daniel Gutierrez. For many new data scientists transitioning into AI and deep learnin…
A comprehensive survey on graph neural networks
A comprehensive survey on graph neural networks Wu et al., arXiv’19 Last year we looked at ‘Relational inductive biases, deep learning, and graph networks,’ where the authors made the case ...
8 Deep Learning Frameworks for Data Science Enthusiasts
With more and more businesses looking to scale up their operations, it has become integral for them to imbibe both machine learning as well as predictive analytics AI coupled with the ...
One Step Closer to Deep Learning on Neuromorphic Hardware
A group of researchers at Sandia National Laboratories have developed a tool that can cross-train standard convolutional neural networks (CNN) to a
Weight Agnostic Neural Networks
Networks that can already (sort of) perform tasks with random weights.
10 Open-Source Tools/Frameworks for Artificial Intelligence
This article gives a list of ten open-source tools/frameworks for AI including TensorFlow, Apache SystemML, Caffe, Apache Mahout, Torch, Neuroph, and OpenNN