77 citations · 124 across the 13 of their papers we have counts for
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stat.ML2021★ 1 cited
Function-space Inference with Sparse Implicit Processes
Simón Rodríguez Santana, Bryan Zaldivar, Daniel Hernández-Lobato
Implicit Processes (IPs) represent a flexible framework that can be used to describe a wide variety of models, from Bayesian neural networks, neural samplers and data generators to…
cs.LG2021★ 1 cited
Input Dependent Sparse Gaussian Processes
Bahram Jafrasteh, Carlos Villacampa-Calvo, Daniel Hernández-Lobato
Gaussian Processes (GPs) are Bayesian models that provide uncertainty estimates associated to the predictions made. They are also very flexible due to their non-parametric nature.…