Expect to hear increasing buzz around graph neural network use cases among hyperscalers in the coming year. Behind the scenes, these are already replacing existing recommendation systems and traveling ...
BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...
Neural Regression Using PyTorch: Defining a Network Dr. James McCaffrey of Microsoft Research presents the second of four machine learning articles that detail a complete end-to-end production-quality ...
Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Graphs are, quite simply, a universal ...
Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
The goal of a regression problem is to predict a single numeric value, for example, predicting the price of a used car based on variables such as mileage, brand and year manufactured. There are ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback