Yordan Hristov

According to our database, Yordan Hristov authored at least 13 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Toward Robust Facial Action Units' Detection.

Jing Yang, Yordan Hristov, Jie Shen, Yiming Lin, Maja Pantic

Proc. IEEE, October, 2023

FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection.

Jing Yang, Jie Shen, Yiming Lin, Yordan Hristov, Maja Pantic

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

2021

Interactive robot learning with human alignment.

Yordan Hristov

PhD thesis, 2021

Automatic Synthesis of Experiment Designs from Probabilistic Environment Specifications.

Craig Innes, Yordan Hristov, Georgios Kamaras, Subramanian Ramamoorthy

CoRR, 2021

Learning from Demonstration with Weakly Supervised Disentanglement.

Yordan Hristov, Subramanian Ramamoorthy

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Composing Diverse Policies for Temporally Extended Tasks.

Daniel Angelov, Yordan Hristov, Michael Burke, Subramanian Ramamoorthy

IEEE Robotics Autom. Lett., 2020

From demonstrations to task-space specifications. Using causal analysis to extract rule parameterization from demonstrations.

Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy

Auton. Agents Multi Agent Syst., 2020

2019

DynoPlan: Combining Motion Planning and Deep Neural Network based Controllers for Safe HRL.

Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy

CoRR, 2019

Disentangled Relational Representations for Explaining and Learning from Demonstration.

Yordan Hristov, Daniel Angelov, Michael Burke, Alex Lascarides, Subramanian Ramamoorthy

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Hybrid system identification using switching density networks.

Michael Burke, Yordan Hristov, Subramanian Ramamoorthy

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Using Causal Analysis to Learn Specifications from Task Demonstrations.

Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Interpretable Latent Spaces for Learning from Demonstration.

Yordan Hristov, Alex Lascarides, Subramanian Ramamoorthy

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Grounding Symbols in Multi-Modal Instructions.

Yordan Hristov, Svetlin Penkov, Alex Lascarides, Subramanian Ramamoorthy

Proceedings of the First Workshop on Language Grounding for Robotics, 2017