2 code implementations • 8 Nov 2020 • James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
As Gaussian processes are used to answer increasingly complex questions, analytic solutions become scarcer and scarcer.
no code implementations • 29 Oct 2020 • Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
Gaussian processes are a versatile framework for learning unknown functions in a manner that permits one to utilize prior information about their properties.
1 code implementation • NeurIPS 2020 • Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Gaussian processes are an effective model class for learning unknown functions, particularly in settings where accurately representing predictive uncertainty is of key importance.
5 code implementations • ICML 2020 • James T. Wilson, Viacheslav Borovitskiy, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth
Gaussian processes are the gold standard for many real-world modeling problems, especially in cases where a model's success hinges upon its ability to faithfully represent predictive uncertainty.