most citedA High-Fidelity Open Embodied Avatar with Lip Syncing and Expression Capabilities

37 citations · 45 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Understanding Failures of Deep Networks via Robust Feature Extraction

Sahil Singla, Besmira Nushi, Shital Shah +2

Traditional evaluation metrics for learned models that report aggregate scores over a test set are insufficient for surfacing important and informative patterns of failure over fea…

cs.LG2020

An Empirical Analysis of Backward Compatibility in Machine Learning Systems

Megha Srivastava, Besmira Nushi, Ece Kamar +2

In many applications of machine learning (ML), updates are performed with the goal of enhancing model performance. However, current practices for updating models rely solely on iso…

cs.LG2020

Safe Reinforcement Learning via Curriculum Induction

Matteo Turchetta, Andrey Kolobov, Shital Shah +2

In safety-critical applications, autonomous agents may need to learn in an environment where mistakes can be very costly. In such settings, the agent needs to behave safely not onl…

cs.LG20208 cited

A System for Real-Time Interactive Analysis of Deep Learning Training

Shital Shah, Roland Fernandez, Steven Drucker

Performing diagnosis or exploratory analysis during the training of deep learning models is challenging but often necessary for making a sequence of decisions guided by the increme…

cs.HC201937 cited

A High-Fidelity Open Embodied Avatar with Lip Syncing and Expression Capabilities

Deepali Aneja, Daniel McDuff, Shital Shah

Embodied avatars as virtual agents have many applications and provide benefits over disembodied agents, allowing non-verbal social and interactional cues to be leveraged, in a simi…