38 citations · 78 across the 22 of their papers we have counts for
5 papers · 1 filter
Stationary Activations for Uncertainty Calibration in Deep Learning
Lassi Meronen, Christabella Irwanto, Arno Solin
We introduce a new family of non-linear neural network activation functions that mimic the properties induced by the widely-used Matérn family of kernels in Gaussian process (GP) m…
Movement-induced Priors for Deep Stereo
Yuxin Hou, Muhammad Kamran Janjua, Juho Kannala +1
We propose a method for fusing stereo disparity estimation with movement-induced prior information. Instead of independent inference frame-by-frame, we formulate the problem as a n…
Fast Variational Learning in State-Space Gaussian Process Models
Paul E. Chang, William J. Wilkinson, Mohammad Emtiyaz Khan +1
Gaussian process (GP) regression with 1D inputs can often be performed in linear time via a stochastic differential equation formulation. However, for non-Gaussian likelihoods, thi…
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes
William J. Wilkinson, Paul E. Chang, Michael Riis Andersen +1
We formulate approximate Bayesian inference in non-conjugate temporal and spatio-temporal Gaussian process models as a simple parameter update rule applied during Kalman smoothing.…
Movement Tracking by Optical Flow Assisted Inertial Navigation
Lassi Meronen, William J. Wilkinson, Arno Solin
Robust and accurate six degree-of-freedom tracking on portable devices remains a challenging problem, especially on small hand-held devices such as smartphones. For improved robust…