Theresa Götz

Orcid: 0000-0001-8751-3404

According to our database1, Theresa Götz authored at least 11 papers between 2015 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
An adaptive binary particle swarm optimization for solving multi-objective convolutional filter pruning problem.
J. Supercomput., August, 2023

Self-supervised representation learning using multimodal Transformer for emotion recognition.
Proceedings of the 8th international Workshop on Sensor-Based Activity Recognition and Artificial Intelligence, 2023

Bio-Signal Based Multimodal Fusion with Bilinear Model for Emotion Recognition.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Transformer-based Self-supervised Representation Learning for Emotion Recognition Using Bio-signal Feature Fusion.
Proceedings of the 11th International Conference on Affective Computing and Intelligent Interaction, ACII 2023, 2023

2022
An optimal-score-based filter pruning for deep convolutional neural networks.
Appl. Intell., 2022

A Simple and Effective Convolutional Filter Pruning based on Filter Dissimilarity Analysis.
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

2021
Automated emotion classification in the early stages of cortical processing: An MEG study.
Artif. Intell. Medicine, 2021

2018
Using PARAFAC2 for Multi-Way Component Analysis of Somatosensory Evoked Magnetic Fields and Somatosensory Evoked Electrical Potentials.
Proceedings of the 10th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2018

A new coupled PARAFAC2 decomposition for joint processing of somatosensory evoked magnetic fields and somatosensory evoked electrical potentials.
Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018

2016
Modality-independent reduction mechanisms of primary sensory evoked fields in a one-back task.
NeuroImage, 2016

2015
Parallel processing of somatosensory information: Evidence from dynamic causal modeling of MEG data.
NeuroImage, 2015


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