Revisiting Wiener's principle of causality - interaction-delay reconstruction using transfer entropy and multivariate analysis on delay-weighted graphs. - Michael Wibral; Patricia Wollstadt; Ulrich Meyer 001; Nicolae Pampu; Viola Priesemann; Raul Vicente (EMBC, 2012)

Efficient transfer entropy analysis of non-stationary neural time series. - Patricia Wollstadt; Mario Martínez-Zarzuela; Raul Vicente; Francisco Javier Díaz Pernas; Michael Wibral (CoRR, 2014)

Reduced predictable information in brain signals in autism spectrum disorder. - Carlos Gómez; Joseph Troy Lizier; Michael Schaum; Patricia Wollstadt; Christine Grützner; Peter Uhlhaas; Christine M. Freitag; Sabine Schlitt; Sven Bölte; Roberto Hornero; Michael Wibral (Frontiers Neuroinformatics, 2014)

Anesthesia-related changes in information transfer may be caused by reduction in local information generation. - Patricia Wollstadt; Kristin K. Sellers; Axel Hutt; Flavio Fröhlich; Michael Wibral (EMBC, 2015)

A Graph Algorithmic Approach to Separate Direct from Indirect Neural Interactions. - Patricia Wollstadt; Ulrich Meyer 001; Michael Wibral (CoRR, 2015)

Quantifying Information Modification in Developing Neural Networks via Partial Information Decomposition. - Michael Wibral; Conor Finn; Patricia Wollstadt; Joseph T. Lizier; Viola Priesemann (Entropy, 2017)

Breakdown of local information processing may underlie isoflurane anesthesia effects. - Patricia Wollstadt; Kristin K. Sellers; Lucas Rudelt; Viola Priesemann; Axel Hutt; Flavio Fröhlich; Michael Wibral (PLoS Comput. Biol., 2017)

Measuring information processing in neural data: The application of transfer entropy in neuroscience. - Patricia Wollstadt (2018)

Learning Time-Series Data of Industrial Design Optimization using Recurrent Neural Networks. - Sneha Saha; Thiago Rios; Stefan Menzel; Bernhard Sendhoff; Thomas Bäck; Xin Yao 001; Zhao Xu 001; Patricia Wollstadt (ICDM Workshops, 2019)

Scalability of Learning Tasks on 3D CAE Models Using Point Cloud Autoencoders. - Thiago Rios; Patricia Wollstadt; Bas van Stein; Thomas Bäck; Zhao Xu 001; Bernhard Sendhoff; Stefan Menzel (SSCI, 2019)

Large-scale directed network inference with multivariate transfer entropy and hierarchical statistical testing. - Leonardo Novelli; Patricia Wollstadt; Pedro A. M. Mediano; Michael Wibral; Joseph T. Lizier (CoRR, 2019)

IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks. - Patricia Wollstadt; Joseph T. Lizier; Raul Vicente; Conor Finn; Mario Martínez-Zarzuela; Pedro A. M. Mediano; Leonardo Novelli; Michael Wibral (J. Open Source Softw., 2019)

A Compact Spectral Descriptor for Shape Deformations. - Skylar Sible; Rodrigo Iza-Teran; Jochen Garcke; Nikola Aulig; Patricia Wollstadt (ECAI, 2020)

Feature Visualization for 3D Point Cloud Autoencoders. - Thiago Rios; Bas van Stein; Stefan Menzel; Thomas Bäck; Bernhard Sendhoff; Patricia Wollstadt (IJCNN, 2020)

The Effects Of Non-linear Operators In Voxel-Based Deep Neural Networks For 3D Style Reconstruction. - Timo Friedrich; Patricia Wollstadt; Stefan Menzel (SSCI, 2020)

Back To Meshes: Optimal Simulation-ready Mesh Prototypes For Autoencoder-based 3D Car Point Clouds. - Thiago Rios; Jiawen Kong; Bas van Stein; Thomas Bäck; Patricia Wollstadt; Bernhard Sendhoff; Stefan Menzel (SSCI, 2020)

Quantifying The Generative Capabilities Of Variational Autoencoders For 3D Car Point Clouds. - Sneha Saha; Stefan Menzel; Leandro L. Minku; Xin Yao 001; Bernhard Sendhoff; Patricia Wollstadt (SSCI, 2020)

Measuring spectrally-resolved information transfer. - Edoardo Pinzuti; Patricia Wollstadt; Aaron J. Gutknecht; Oliver Tüscher; Michael Wibral (PLoS Comput. Biol., 2020)

Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders. - Thiago Rios; Bas van Stein; Patricia Wollstadt; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (CEC, 2021)

Exploiting Generative Models for Performance Predictions of 3D Car Designs. - Sneha Saha; Thiago Rios; Leandro L. Minku; Bas van Stein; Patricia Wollstadt; Xin Yao 001; Thomas Bäck; Bernhard Sendhoff; Stefan Menzel (SSCI, 2021)

Interaction-Aware Sensitivity Analysis for Aerodynamic Optimization Results using Information Theory. - Patricia Wollstadt; Sebastian Schmitt (SSCI, 2021)

A partial information decomposition for discrete and continuous variables. - Kyle Schick-Poland; Abdullah Makkeh; Aaron J. Gutknecht; Patricia Wollstadt; Anja Sturm; Michael Wibral (CoRR, 2021)

Quantifying the Predictability of Visual Scanpaths Using Active Information Storage. - Patricia Wollstadt; Martina Hasenjäger; Christiane B. Wiebel-Herboth (Entropy, 2021)

Poster: Quantifying Cooperation Between Artificial Agents Using Information Theory. - Patricia Wollstadt; Matti Krüger (HHAI, 2022)

Understanding Concept Identification as Consistent Data Clustering Across Multiple Feature Spaces. - Felix Lanfermann; Sebastian Schmitt; Patricia Wollstadt (ICDM (Workshops), 2022)

Quantifying cooperation between artificial agents using synergistic information. - Patricia Wollstadt; Matti Krüger (SSCI, 2022)

CarHoods10k: An Industry-Grade Data Set for Representation Learning and Design Optimization in Engineering Applications. - Patricia Wollstadt; Mariusz Bujny; Satchit Ramnath; Jami J. Shah; Duane Detwiler; Stefan Menzel (IEEE Trans. Evol. Comput., 2022)

Enhancing Trust in Smart Charging Agents - The Role of Traceability for Human-Agent-Cooperation. - Christiane Attig; Tim Schrills; Markus Gödker; Patricia Wollstadt; Christiane B. Wiebel-Herboth; André Calero Valdez; Thomas Franke (HCI (53), 2023)

Who's in Charge of Charging? Investigating Human-Machine-Cooperation in Smart Charging of Electric Vehicles. - Meike E. Kühne; Christiane B. Wiebel-Herboth; Patricia Wollstadt; André Calero Valdez; Thomas Franke (HCI (38), 2023)

Quantifying Cooperation Between Rule-Based Hanabi Agents Using Information Theory. - Patricia Wollstadt; Matti Krüger; Christiane B. Wiebel-Herboth (HHAI, 2023)

Precision and Recall Reject Curves for Classification. - Lydia Fischer; Patricia Wollstadt (CoRR, 2023)

Partial Information Decomposition for Continuous Variables based on Shared Exclusions: Analytical Formulation and Estimation. - David A. Ehrlich; Kyle Schick-Poland; Abdullah Makkeh; Felix Lanfermann; Patricia Wollstadt; Michael Wibral (CoRR, 2023)

A Rigorous Information-Theoretic Definition of Redundancy and Relevancy in Feature Selection Based on (Partial) Information Decomposition. - Patricia Wollstadt; Sebastian Schmitt; Michael Wibral (J. Mach. Learn. Res., 2023)

Information theoretic evidence for layer- and frequency-specific changes in cortical information processing under anesthesia. - Edoardo Pinzuti; Patricia Wollstadt; Oliver Tüscher; Michael Wibral (PLoS Comput. Biol., 2023)

Information-theoretic analyses of neural data to minimize the effect of researchers' assumptions in predictive coding studies. - Patricia Wollstadt; Daniel L. Rathbun; W. Martin Usrey; André Moraes Bastos; Michael Lindner; Viola Priesemann; Michael Wibral (PLoS Comput. Biol., 2023)

More than Task Performance: Developing New Criteria for Successful Human-AI Teaming Using the Cooperative Card Game Hanabi. - Christiane Attig; Patricia Wollstadt; Tim Schrills; Thomas Franke; Christiane B. Wiebel-Herboth (CHI Extended Abstracts, 2024)

Precision and Recall Reject Curves. - Lydia Fischer; Patricia Wollstadt (WSOM+, 2024)

A Real-World Energy Management Dataset from a Smart Company Building for Optimization and Machine Learning. - Jens Engel; Andrea Castellani; Patricia Wollstadt; Felix Lanfermann; Thomas Schmitt; Sebastian Schmitt; Lydia Fischer; Steffen Limmer; David Luttropp; Florian Jomrich; René Unger; Tobias Rodemann (CoRR, 2025)

Assistax: A Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics. - Leonard Hinckeldey; Elliot Fosong; Elle Miller; Rimvydas Rubavicius; Trevor McInroe; Patricia Wollstadt; Christiane B. Wiebel-Herboth; Subramanian Ramamoorthy; Stefano V. Albrecht (CoRR, 2025)