19 citations · 38 across the 10 of their papers we have counts for
12 papers
Seamless Interaction: Dyadic Audiovisual Motion Modeling and Large-Scale Dataset
Vasu Agrawal, Akinniyi Akinyemi, Kathryn Alvero +81
Human communication involves a complex interplay of verbal and nonverbal signals, essential for conveying meaning and achieving interpersonal goals. To develop socially intelligent…
FAN-Trans: Online Knowledge Distillation for Facial Action Unit Detection
Jing Yang, Jie Shen, Yiming Lin +2
Due to its importance in facial behaviour analysis, facial action unit (AU) detection has attracted increasing attention from the research community. Leveraging the online knowledg…
Automatic Synthesis of Experiment Designs from Probabilistic Environment Specifications
Craig Innes, Yordan Hristov, Georgios Kamaras +1
This paper presents an extension to the probabilistic programming language ProbRobScene, allowing users to automatically synthesize uniform experiment designs directly from environ…
From Demonstrations to Task-Space Specifications: Using Causal Analysis to Extract Rule Parameterization from Demonstrations
Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy
Learning models of user behaviour is an important problem that is broadly applicable across many application domains requiring human-robot interaction. In this work, we show that i…
Learning from Demonstration with Weakly Supervised Disentanglement
Yordan Hristov, Subramanian Ramamoorthy
Robotic manipulation tasks, such as wiping with a soft sponge, require control from multiple rich sensory modalities. Human-robot interaction, aimed at teaching robots, is difficul…
Disentangled Relational Representations for Explaining and Learning from Demonstration
Yordan Hristov, Daniel Angelov, Michael Burke +2
Learning from demonstration is an effective method for human users to instruct desired robot behaviour. However, for most non-trivial tasks of practical interest, efficient learnin…
Composing Diverse Policies for Temporally Extended Tasks
Daniel Angelov, Yordan Hristov, Michael Burke +1
Robot control policies for temporally extended and sequenced tasks are often characterized by discontinuous switches between different local dynamics. These change-points are often…
Hybrid system identification using switching density networks
Michael Burke, Yordan Hristov, Subramanian Ramamoorthy
Behaviour cloning is a commonly used strategy for imitation learning and can be extremely effective in constrained domains. However, in cases where the dynamics of an environment m…
DynoPlan: Combining Motion Planning and Deep Neural Network based Controllers for Safe HRL
Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy
Many realistic robotics tasks are best solved compositionally, through control architectures that sequentially invoke primitives and achieve error correction through the use of loo…
Using Causal Analysis to Learn Specifications from Task Demonstrations
Daniel Angelov, Yordan Hristov, Subramanian Ramamoorthy
Learning models of user behaviour is an important problem that is broadly applicable across many application domains requiring human-robot interaction. In this work we show that it…
Interpretable Latent Spaces for Learning from Demonstration
Yordan Hristov, Alex Lascarides, Subramanian Ramamoorthy
Effective human-robot interaction, such as in robot learning from human demonstration, requires the learning agent to be able to ground abstract concepts (such as those contained w…
Grounding Symbols in Multi-Modal Instructions
Yordan Hristov, Svetlin Penkov, Alex Lascarides +1
As robots begin to cohabit with humans in semi-structured environments, the need arises to understand instructions involving rich variability---for instance, learning to ground sym…