Abstract: Data augmentation plays a crucial role in data-driven geoscience research by minimizing sampling costs and improving the generalization and predictive accuracy of models utilized in mineral ...

[1] F. Scarselli, M. Gori, A.C. Tsoi, M. Hagenbuchner, and G. Monfardini. The graph neural network model. IEEE Transactions on Neural Networks, 20(1):61 80, 2009.

teras (short for Tabular Keras) is a unified deep learning library for Tabular Data that aims to be your one stop for everything related to deep learing with tabular data. IMPORTANT teras v0.3 is now ...

Abstract: Latent graph structure and stimulus of graph-structured data contain critical private information, such as brain disorders in functional magnetic resonance imaging data, and can be exploited ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...