NEW YORK & LONDON--(BUSINESS WIRE)--The Visualize Group (“Visualize”), a private investment firm focused on investing in mission-critical, services-based companies, today announced that it has agreed ...

Abstract: Effectively estimating the uncertainty attached to neural network predictions thus becomes essential to improve robustness, reliability, and trustworthiness. This paper provides an overview ...

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...

Docker eliminates dependency hell (pycapnp builds, Julia packages, CUDA) and makes the pipeline reproducible. GPU training in Docker requires nvidia-container-toolkit ...

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 ...