2 papers
cs.LG2023
Creating Probabilistic Forecasts from Arbitrary Deterministic Forecasts using Conditional Invertible Neural Networks
Kaleb Phipps, Benedikt Heidrich, Marian Turowski +3
In various applications, probabilistic forecasts are required to quantify the inherent uncertainty associated with the forecast. However, numerous modern forecasting methods are st…
cs.LG2021
Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models
Daniel Bogdoll, Johannes Jestram, Jonas Rauch +3
In the foreseeable future, autonomous vehicles will require human assistance in situations they can not resolve on their own. In such scenarios, remote assistance from a human can…