Search Results for author: Gordon Pipa

Found 9 papers, 6 papers with code

Fast Concept Mapping: The Emergence of Human Abilities in Artificial Neural Networks when Learning Embodied and Self-Supervised

1 code implementation3 Feb 2021 Viviane Clay, Peter König, Gordon Pipa, Kai-Uwe Kühnberger

Following this, the representations learned through interaction with the world can be used to associate semantic concepts such as different types of doors.

object-detection Object Detection

WestDrive X LoopAR: An open-access virtual reality project in Unity for evaluating user interaction methods during TOR

no code implementations22 Dec 2020 Farbod N. Nezami, Maximilian A. Wächter, Nora Maleki, Philipp Spaniol, Lea M. Kühne, Anke Haas, Johannes M. Pingel, Linus Tiemann, Frederik Nienhaus, Lynn Keller, Sabine König, Peter König, Gordon Pipa

The presented project contains all needed functionalities for realistic traffic behavior, cars, and pedestrians, as well as a large, open-source, scriptable, and modular VR environment.

Human-Computer Interaction

Reliability and comparability of human brain structural covariance networks

1 code implementation28 Nov 2019 Jona Carmon, Jil Heege, Joe H Necus, Thomas W Owen, Gordon Pipa, Marcus Kaiser, Peter N Taylor, Yujiang Wang

In terms of comparability, our results show substantial differences in the structural covariance matrix between data sets of age- and sex-matched healthy human adults.

Neurons and Cognition Quantitative Methods

Learning Semantically Meaningful Representations Through Embodiment

no code implementations25 Sep 2019 Viviane Clay, Peter König, Kai-Uwe Kühnberger, Gordon Pipa

How do humans acquire a meaningful understanding of the world with little to no supervision or semantic labels provided by the environment?

Predicting epileptic seizures using nonnegative matrix factorization

1 code implementation medrxiv, PLOS ONE (under review) 2019 Olivera Stojanović, Gordon Pipa

The resulting method yields a computationally and conceptually simple, interpretable model of EEG signals of preictal and interictal states, which shows a good performance for the task of seizure prediction.

EEG Epilepsy Prediction +1

Adaptive Blending Units: Trainable Activation Functions for Deep Neural Networks

no code implementations26 Jun 2018 Leon René Sütfeld, Flemming Brieger, Holger Finger, Sonja Füllhase, Gordon Pipa

Since ABUs learn the shape, as well as the overall scaling of the activation function, we also analyze the effects of adaptive scaling in common activation functions.

Cortical Spike Synchrony as a Measure of Input Familiarity

1 code implementation10 Sep 2017 Clemens Korndörfer, Ekkehard Ullner, Jordi García-Ojalvo, Gordon Pipa

Spike synchrony, which occurs in various cortical areas in response to specific perception, action and memory tasks, has sparked a long-standing debate on the nature of temporal organization in cortex.

Neurons and Cognition

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