Judith Butepage | DeepAI

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∙ 03/04/2022

Evaluating Local Model-Agnostic Explanations of Learning to Rank Models with Decision Paths

Local explanations of learning-to-rank (LTR) models are thought to extra...

0 Amir Hossein Akhavan Rahnama, et al. ∙

∙ 06/04/2021

Evaluation of Local Model-Agnostic Explanations Using Ground Truth

Explanation techniques are commonly evaluated using human-grounded metho...

0 Amir Hossein Akhavan Rahnama, et al. ∙

∙ 03/26/2020

Fashion Landmark Detection and Category Classification for Robotics

Research on automated, image based identification of clothing categories...

10 Thomas Ziegler, et al. ∙

∙ 10/14/2019

Imitating by generating: deep generative models for imitation of interactive tasks

To coordinate actions with an interaction partner requires a constant ex...

17 Judith Butepage, et al. ∙

∙ 09/24/2018

Classify, predict, detect, anticipate and synthesize: Hierarchical recurrent latent variable models for human activity modeling

Human activity modeling operates on two levels: high-level action modeli...

0 Judith Butepage, et al. ∙

∙ 09/19/2018

Detect, anticipate and generate: Semi-supervised recurrent latent variable models for human activity modeling

Successful Human-Robot collaboration requires a predictive model of huma...

0 Judith Butepage, et al. ∙

∙ 11/15/2017

Advances in Variational Inference

Many modern unsupervised or semi-supervised machine learning algorithms ...

0 Cheng Zhang, et al. ∙

∙ 02/27/2017

Anticipating many futures: Online human motion prediction and synthesis for human-robot collaboration

Fluent and safe interactions of humans and robots require both partners ...

0 Judith Butepage, et al. ∙

∙ 02/24/2017

Deep representation learning for human motion prediction and classification

Generative models of 3D human motion are often restricted to a small num...

0 Judith Butepage, et al. ∙

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