Principled Simplicial Neural Networks for Trajectory Prediction

Principled Simplicial Neural Networks for Trajectory Prediction

Explore principled simplicial neural networks for trajectory prediction in this comprehensive webinar presented by Santiago Segarra from Rice University. Delve into advanced concepts as part of the Data sciEnce on GrAphS (DEGAS) Webinar Series, organized in collaboration with the IEEE Signal Processing Society Data Science Initiative. Gain valuable insights into cutting-edge techniques for predicting trajectories using simplicial neural networks, and understand their applications in various fields. Learn from an expert in the field as you navigate through this 72-minute presentation, which offers a deep dive into the theoretical foundations and practical implementations of this innovative approach to trajectory prediction.