activity
20152023
most citedHow model accuracy and explanation fidelity influence user trust

64 citations · 101 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023

Diffusing More Objects for Semi-Supervised Domain Adaptation with Less Labeling

Leander van den Heuvel, Gertjan Burghouts, David W. Zhang +2

For object detection, it is possible to view the prediction of bounding boxes as a reverse diffusion process. Using a diffusion model, the random bounding boxes are iteratively ref…

cs.NE2023

Feature Attribution Explanations for Spiking Neural Networks

Elisa Nguyen, Meike Nauta, Gwenn Englebienne +1

Third-generation artificial neural networks, Spiking Neural Networks (SNNs), can be efficiently implemented on hardware. Their implementation on neuromorphic chips opens a broad ra…

cs.CY2019★ 64 cited

How model accuracy and explanation fidelity influence user trust

Andrea Papenmeier, Gwenn Englebienne, Christin Seifert

Machine learning systems have become popular in fields such as marketing, financing, or data mining. While they are highly accurate, complex machine learning systems pose challenge…

cs.CL2017★ 9 cited

Learning spectro-temporal features with 3D CNNs for speech emotion recognition

Jaebok Kim, Khiet P. Truong, Gwenn Englebienne +1

In this paper, we propose to use deep 3-dimensional convolutional networks (3D CNNs) in order to address the challenge of modelling spectro-temporal dynamics for speech emotion rec…

cs.CL2017★ 17 cited

Towards Speech Emotion Recognition "in the wild" using Aggregated Corpora and Deep Multi-Task Learning

Jaebok Kim, Gwenn Englebienne, Khiet P. Truong +1

One of the challenges in Speech Emotion Recognition (SER) "in the wild" is the large mismatch between training and test data (e.g. speakers and tasks). In order to improve the gene…

cs.DL2015★ 11 cited

Ariadne's Thread - Interactive Navigation in a World of Networked Information

Rob Koopman, Shenghui Wang, Andrea Scharnhorst +1

This work-in-progress paper introduces an interface for the interactive visual exploration of the context of queries using the ArticleFirst database, a product of OCLC. We describe…