Reasoning about Unforeseen Possibilities During Policy Learning. - Craig Innes; Alex Lascarides; Stefano V. Albrecht; Subramanian Ramamoorthy; Benjamin Rosman (CoRR, 2018)

Learning Structured Decision Problems with Unawareness. - Craig Innes; Alex Lascarides (ICML, 2019)

Learning Factored Markov Decision Processes with Unawareness. - Craig Innes; Alex Lascarides (UAI, 2019)

Learning to make decisions with unforeseen possibilities. - Craig Innes (2019)

Elaborating on Learned Demonstrations with Temporal Logic Specifications. - Craig Innes; Subramanian Ramamoorthy (Robotics: Science and Systems, 2020)

Learning robotic ultrasound scanning using probabilistic temporal ranking. - Michael Burke; Katie Lu; Daniel Angelov; Arturas Straizys; Craig Innes; Kartic Subr; Subramanian Ramamoorthy (CoRR, 2020)

ProbRobScene: A Probabilistic Specification Language for 3D Robotic Manipulation Environments. - Craig Innes; Subramanian Ramamoorthy (ICRA, 2021)

Automatic Synthesis of Experiment Designs from Probabilistic Environment Specifications. - Craig Innes; Yordan Hristov; Georgios Kamaras; Subramanian Ramamoorthy (CoRR, 2021)

Robust Learning from Observation with Model Misspecification. - Luca Viano; Yu-Ting Huang 003; Parameswaran Kamalaruban; Craig Innes; Subramanian Ramamoorthy; Adrian Weller (AAMAS, 2022)

Automated Testing With Temporal Logic Specifications for Robotic Controllers Using Adaptive Experiment Design. - Craig Innes; Subramanian Ramamoorthy (ICRA, 2022)

Learning physics-informed simulation models for soft robotic manipulation: A case study with dielectric elastomer actuators. - Manu Lahariya; Craig Innes; Chris Develder; Subramanian Ramamoorthy (IROS, 2022)

Risk-Driven Design of Perception Systems. - Anthony Corso 001; Sydney M. Katz; Craig Innes; Xin Du 006; Subramanian Ramamoorthy; Mykel J. Kochenderfer (NeurIPS, 2022)

Testing Rare Downstream Safety Violations via Upstream Adaptive Sampling of Perception Error Models. - Craig Innes; Subramanian Ramamoorthy (ICRA, 2023)

Anticipating Accidents through Reasoned Simulation. - Craig Innes; Andrew Ireland; Yuhui Lin; Subramanian Ramamoorthy (TAS, 2023)

Learning rewards from exploratory demonstrations using probabilistic temporal ranking. - Michael Burke; Katie Lu; Daniel Angelov; Arturas Straizys; Craig Innes; Kartic Subr; Subramanian Ramamoorthy (Auton. Robots, 2023)

Dialogue-based generation of self-driving simulation scenarios using Large Language Models. - Antonio Valerio Miceli Barone; Alex Lascarides; Craig Innes (CoRR, 2023)

Conformance Checking of Fuzzy Logs Against Declarative Temporal Specifications. - Ivan Donadello; Paolo Felli; Craig Innes; Fabrizio Maria Maggi; Marco Montali (BPM, 2024)

Adaptive Splitting of Reusable Temporal Monitors for Rare Traffic Violations. - Craig Innes; Subramanian Ramamoorthy (IROS, 2024)

Unobtrusive Monitoring of Physical Weakness: A Simulated Approach. - Longfei Chen; Muhammad Ahmed Raza; Craig Innes; Subramanian Ramamoorthy; Robert B. Fisher (CoRR, 2024)