GitHub

Internet-scale Neural Networks

Welcome! Bittensor is an open source platform on which you can produce competitive digital commodities. These digital commodities can be machine intelligence, storage space, compute power, protein ...
IEEE

End-to-end Graph Learning Approach for Cognitive Diagnosis of Student Tutorial

Abstract: Cognitive diagnosis (CD) utilizes students' existing studying records to estimate their mastery of unknown knowledge concepts, which is vital for evaluating their learning abilities.
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
Oak Ridge National Lab

GSplit: Scaling Graph Neural Network Training on Large Graphs via Split-Parallelism...

Proceedings of The Eighth Annual Conference on Machine Learning and Systems Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their ...
IEEE

Wasserstein Graph Neural Networks for Graphs With Missing Attributes

Abstract: Missing node attributes pose a common problem in real-world graphs, impacting the performance of graph neural networks’ representation learning. Existing GNNs often struggle to effectively ...
Wired

Liquid AI Is Redesigning the Neural Network

Artificial intelligence might now be solving advanced math, performing complex reasoning, and even using personal computers, but today’s algorithms could still learn a thing or two from microscopic ...