Embedding Symbolic Temporal Knowledge into Deep Sequential Models
We embed symbolic knowledge expressed as linear temporal logic (LTL) and use these embeddings to guide the training of deep sequential models.
Collaborative, Learning, and Adaptive Robots Lab at NUS
We embed symbolic knowledge expressed as linear temporal logic (LTL) and use these embeddings to guide the training of deep sequential models.
Leveraging prior symbolic knowledge to improve the performance of deep models.