380 citations · 1.1k across the 43 of their papers we have counts for
3 papers · 2 filters
Black box variational inference for state space models
Evan Archer, Il Memming Park, Lars Buesing +2
Latent variable time-series models are among the most heavily used tools from machine learning and applied statistics. These models have the advantage of learning latent structure…
Neuroprosthetic decoder training as imitation learning
Josh Merel, David Carlson, Liam Paninski +1
Neuroprosthetic brain-computer interfaces function via an algorithm which decodes neural activity of the user into movements of an end effector, such as a cursor or robotic arm. In…
Sparse Probit Linear Mixed Model
Stephan Mandt, Florian Wenzel, Shinichi Nakajima +3
Linear Mixed Models (LMMs) are important tools in statistical genetics. When used for feature selection, they allow to find a sparse set of genetic traits that best predict a conti…