63 citations · 143 across the 20 of their papers we have counts for
3 papers · 1 filter
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters
Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato
While deep neural networks are a highly successful model class, their large memory footprint puts considerable strain on energy consumption, communication bandwidth, and storage re…
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo
Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes
Deep Gaussian Processes (DGPs) are hierarchical generalizations of Gaussian Processes that combine well calibrated uncertainty estimates with the high flexibility of multilayer mod…
Deep Gaussian Processes with Decoupled Inducing Inputs
Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes
Deep Gaussian Processes (DGP) are hierarchical generalizations of Gaussian Processes (GP) that have proven to work effectively on a multiple supervised regression tasks. They combi…