ResearchTrend.AI
Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes

Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes

Sebastian Kram
Christopher Kraus
Tobias Feigl
Maximilian Stahlke
J. Robert
Christopher Mutschler
ArXiv (abs)PDFHTML

Papers citing "Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes"

4 / 4 papers shown
Title
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration
Jacob R. Gardner
Geoff Pleiss
D. Bindel
Kilian Q. Weinberger
A. Wilson
GP
136
1,100
0
28 Sep 2018
Deep learning for time series classification: a review
Deep learning for time series classification: a review
Hassan Ismail Fawaz
Germain Forestier
J. Weber
L. Idoumghar
Pierre-Alain Muller
AI4TSAI4CE
323
2,698
0
12 Sep 2018
Scalable Magnetic Field SLAM in 3D Using Gaussian Process Maps
Scalable Magnetic Field SLAM in 3D Using Gaussian Process Maps
Manon Kok
Arno Solin
44
68
0
05 Apr 2018
A Belief Propagation Algorithm for Multipath-Based SLAM
A Belief Propagation Algorithm for Multipath-Based SLAM
E. Leitinger
Florian Meyer
F. Hlawatsch
K. Witrisal
Fredrik Tufvesson
M. Win
62
191
0
13 Jan 2018

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.