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ORCIDYordan Hristov
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2020 – today
- 2023
[j3]Jing Yang
, Yordan Hristov, Jie Shen, Yiming Lin, Maja Pantic:
Toward Robust Facial Action Units' Detection. Proc. IEEE 111(10): 1198-1214 (2023)- [c7]Jing Yang, Jie Shen, Yiming Lin, Yordan Hristov, Maja Pantic:
FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection. WACV 2023: 6008-6016 - 2022
- [i11]Jing Yang, Jie Shen, Yiming Lin, Yordan Hristov, Maja Pantic:
FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection. CoRR abs/2211.06143 (2022) - 2021
- [b1]Yordan Hristov:
Interactive robot learning with human alignment. University of Edinburgh, UK, 2021 - [c6]Yordan Hristov, Subramanian Ramamoorthy:
Learning from Demonstration with Weakly Supervised Disentanglement. ICLR 2021 - [i10]Craig Innes, Yordan Hristov, Georgios Kamaras, Subramanian Ramamoorthy:
Automatic Synthesis of Experiment Designs from Probabilistic Environment Specifications. CoRR abs/2107.00093 (2021) - 2020
- [j2]Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy:
From demonstrations to task-space specifications. Using causal analysis to extract rule parameterization from demonstrations. Auton. Agents Multi Agent Syst. 34(2): 45 (2020) - [j1]Daniel Angelov, Yordan Hristov, Michael Burke, Subramanian Ramamoorthy:
Composing Diverse Policies for Temporally Extended Tasks. IEEE Robotics Autom. Lett. 5(2): 2658-2665 (2020) - [i9]Yordan Hristov, Subramanian Ramamoorthy:
Learning from Demonstration with Weakly Supervised Disentanglement. CoRR abs/2006.09107 (2020) - [i8]Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy:
From Demonstrations to Task-Space Specifications: Using Causal Analysis to Extract Rule Parameterization from Demonstrations. CoRR abs/2006.11300 (2020)
2010 – 2019
- 2019
- [c5]Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy:
Using Causal Analysis to Learn Specifications from Task Demonstrations. AAMAS 2019: 1341-1349 - [c4]Michael Burke, Yordan Hristov, Subramanian Ramamoorthy:
Hybrid system identification using switching density networks. CoRL 2019: 172-181 - [c3]Yordan Hristov, Daniel Angelov, Michael Burke, Alex Lascarides, Subramanian Ramamoorthy:
Disentangled Relational Representations for Explaining and Learning from Demonstration. CoRL 2019: 870-884 - [i7]Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy:
Using Causal Analysis to Learn Specifications from Task Demonstrations. CoRR abs/1903.01267 (2019) - [i6]Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy:
DynoPlan: Combining Motion Planning and Deep Neural Network based Controllers for Safe HRL. CoRR abs/1906.10099 (2019) - [i5]Michael Burke, Yordan Hristov, Subramanian Ramamoorthy:
Hybrid system identification using switching density networks. CoRR abs/1907.04360 (2019) - [i4]Daniel Angelov, Yordan Hristov, Michael Burke, Subramanian Ramamoorthy:
Composing Diverse Policies for Temporally Extended Tasks. CoRR abs/1907.08199 (2019) - [i3]Yordan Hristov, Daniel Angelov, Michael Burke, Alex Lascarides, Subramanian Ramamoorthy:
Disentangled Relational Representations for Explaining and Learning from Demonstration. CoRR abs/1907.13627 (2019) - 2018
- [c2]Yordan Hristov, Alex Lascarides, Subramanian Ramamoorthy:
Interpretable Latent Spaces for Learning from Demonstration. CoRL 2018: 957-968 - [i2]Yordan Hristov, Alex Lascarides, Subramanian Ramamoorthy:
Interpretable Latent Spaces for Learning from Demonstration. CoRR abs/1807.06583 (2018) - 2017
- [c1]Yordan Hristov, Svetlin Penkov, Alex Lascarides, Subramanian Ramamoorthy:
Grounding Symbols in Multi-Modal Instructions. RoboNLP@ACL 2017: 49-57 - [i1]Yordan Hristov, Svetlin Penkov, Alex Lascarides, Subramanian Ramamoorthy:
Grounding Symbols in Multi-Modal Instructions. CoRR abs/1706.00355 (2017)
Coauthor Index
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