Large-Scale Spatio-Temporal Reasoning and Learning
| Title: |
Large-Scale Spatio-Temporal Reasoning and Learning |
| DNr: |
Berzelius-2023-1 |
| Project Type: |
LiU Berzelius |
| Principal Investigator: |
Fredrik Heintz <fredrik.heintz@liu.se> |
| Affiliation: |
Linköpings universitet |
| Duration: |
2023-01-10 – 2023-08-01 |
| Classification: |
10201 |
| Homepage: |
https://www.ida.liu.se/~frehe08/ |
| Keywords: |
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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.