April 25 - - October 25, 2023
Our work POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning has been accepted at the Transactions on Machine Learning Research (TMLR)!
March 30 - - April 30, 2023
Our joint work Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposure was accepted to Biofouling. Thanks for the great effort to our colleagues from Ruhr-Univerisität Bochum and Florida Tech! Code is available on Github.
February 07, 2023
The TNT is excited to announce that we are part of the Horizon Europe funded project Satellites for Wilderness Inspection and Forest Threat Tracking (SWIFTT). The project's goal is to develop powerful machine learning models as a backend for a platform which helps forest managers to detect threats to their forests in an affordable and simple manner. SWIFTT will be based on the remote sensing data provided by the Copernicus programme. The TNT's primary role will be developing a model for wildfire risk prediction at a high spatial resolution. SWIFTT's first press release can be found here.
January 30 - - June 15, 2023
Our paper Deep Reinforcement Learning for Autonomous Driving using High-Level Heterogeneous Graph Representations has been accepted to ICRA 2023! You can find the accepted version here. Our implementation is published here.
