4 papers
Last Layer Hamiltonian Monte Carlo
Koen Vellenga, H. Joe Steinhauer, Göran Falkman +2
We explore the use of Hamiltonian Monte Carlo (HMC) sampling as a probabilistic last layer approach for deep neural networks (DNNs). While HMC is widely regarded as a gold standard…
Maximum Likelihood Estimation of the Vector AutoRegressive To Anything (VARTA) model
Jonas Andersson, Dimitris Karlis
The literature on multivariate time series is, largely, limited to either models based on the multivariate Gaussian distribution or models specifically developed for a given applic…
Latent Uncertainty Representations for Video-based Driver Action and Intention Recognition
Koen Vellenga, H. Joe Steinhauer, Jonas Andersson +1
Deep neural networks (DNNs) are increasingly applied to safety-critical tasks in resource-constrained environments, such as video-based driver action and intention recognition. Whi…
An integrated process for design and control of lunar robotics using AI and simulation
Daniel Lindmark, Jonas Andersson, Kenneth Bodin +4
We envision an integrated process for developing lunar construction equipment, where physical design and control are explored in parallel. In this paper, we describe a technical fr…