Machine Learning
Differentiable Logic Layer for Rule Guided Trajectory Prediction
Learning An Explainable Trajectory Generator Using The Automaton Generative Network (AGN)
Vehicle Trajectory Prediction Using Generative Adversarial Network With Temporal Logic Syntax Tree Features
Deep Bayesian Nonparametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior
Brandon Araki, Kiran Vodrahalli, Thomas Leech, Cristian Ioan Vasile, Mark Donahue, and Daniela Rus. Deep Bayesian Non-parametric Learning of Rules and Plans from Demonstrations with a Learned Automaton Prior. In AAAI Conference on Artificial Intellifence, New York, NY, USA, July 2020.
Learning to Plan with Logical Automata
Brandon Araki, Kiran Vodrahalli, Cristian Ioan Vasile, and Daniela Rus. Learning to Plan with Logical Automata. In Infer to Control, Workshop on Probabilistic Reinforcement Learning and Structured Control (Infer2Control), NIPS, page Poster, Montreal, Canada, December 2018. link.
Learning to Plan with Logical Automata
Brandon Araki, Kiran Vodrahalli, Thomas Leech, Cristian Ioan Vasile, Mark Donahue, and Daniela Rus. Learning to Plan with Logical Automata. In Robotics: Science and Systems Conference (RSS), pages 1–9, Messe Freiburg, Germany, June 2019. link.
A Decision Tree Approach to Data Classification using Signal Temporal Logic
Giuseppe Bombara, Cristian-Ioan Vasile, Francisco Penedo Alvarez, Yasuoka Hirotoshi, and Calin Belta. A Decision Tree Approach to Data Classification using Signal Temporal Logic. In Hybrid Systems: Computation and Control (HSCC), pages 1–10, Vienna, Austria, April 2016. doi:10.1145/2883817.2883843.
