Large-Scale Spatio-Temporal Reasoning and Learning
	  
	  
| Title: | 
    Large-Scale Spatio-Temporal Reasoning and Learning | 
| DNr: | 
    Berzelius-2023-214 | 
| Project Type: | 
    LiU Berzelius | 
| Principal Investigator: | 
    Fredrik Heintz <fredrik.heintz@liu.se> | 
| Affiliation: | 
    Linköpings universitet | 
| Duration: | 
    2023-08-31 – 2024-03-01 | 
| Classification: | 
    10201   | 
| Homepage: | 
    https://www.ida.liu.se/~frehe08/ | 
| Keywords: | 
     | 
  Abstract
  The goal of our research is to develop novel reasoning and learning methods for large-scale spatio-temporal applications. This includes for example time-series learning (diffusion models and GANs) and multi-agent reinforcement learning. The expected scientific impact is publications in top-level conferences and the expected soecity impact is more effective decision-making methods for autonomous systems such as unmanned aircraft, more effective transporation solutions and methods for privacy-preserving synthetic data generation.