Sebastian Otte

CoRR, 2024

2023

Physical Domain Reconstruction with Finite Volume Neural Networks.

[BibT_eX]

[DOI]

Appl. Artif. Intell., December, 2023

The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.

[BibT_eX]

[DOI]

Neural Networks, September, 2023

Extending the Omniglot Challenge: Imitating Handwriting Styles on a New Sequential Data Set.

[BibT_eX]

[DOI]

IEEE Trans. Cogn. Dev. Syst., 2023

Loci-Segmented: Improving Scene Segmentation Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Looping LOCI: Developing Object Permanence from Videos.

[BibT_eX]

[DOI]

CoRR, 2023

Inductive biases in deep learning models for weather prediction.

[BibT_eX]

[DOI]

CoRR, 2023

Learning What and Where: Disentangling Location and Identity Tracking Without Supervision.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Replication Data for: Learning Groundwater Contaminant Diffusion-Sorption Processes with a Finite Volume Neural Network.

[BibT_eX]

[DOI]

Dataset, November, 2022

Inference of affordances and active motor control in simulated agents.

[BibT_eX]

[DOI]

Frontiers Neurorobotics, September, 2022

Inference of time series components by online co-evolution.

[BibT_eX]

[DOI]

Danil Koryakin

Genet. Program. Evolvable Mach., 2022

Generating Sparse Counterfactual Explanations For Multivariate Time Series.

[BibT_eX]

[DOI]

CoRR, 2022

Learning What and Where - Unsupervised Disentangling Location and Identity Tracking.

[BibT_eX]

[DOI]

CoRR, 2022

Composing Partial Differential Equations with Physics-Aware Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Binding Dancers Into Attractors.

[BibT_eX]

[DOI]

Franziska Kaltenberger

Proceedings of the IEEE International Conference on Development and Learning, 2022

A Taxonomy of Recurrent Learning Rules.

[BibT_eX]

[DOI]

Guillermo Martín-Sánchez

Sander M. Bohté

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Efficient LSTM Training with Eligibility Traces.

[BibT_eX]

[DOI]

Michael Hoyer

Shahram Eivazi

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

Infering Boundary Conditions in Finite Volume Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021

Finite Volume Neural Network: Modeling Subsurface Contaminant Transport.

[BibT_eX]

[DOI]

CoRR, 2021

Many-Joint Robot Arm Control with Recurrent Spiking Neural Networks.

[BibT_eX]

[DOI]

Manuel Traub

Robert Legenstein

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Gestalt Perception of Biological Motion: A Generative Artificial Neural Network Model.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Development and Learning, 2021

Dynamic Action Inference with Recurrent Spiking Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Binding and Perspective Taking as Inference in a Generative Neural Network Model.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Early Recognition of Ball Catching Success in Clinical Trials with RNN-Based Predictive Classification.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Latent State Inference in a Spatiotemporal Generative Model.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Fostering Compositionality in Latent, Generative Encodings to Solve the Omniglot Challenge.

[BibT_eX]

[DOI]

Sarah Fabi

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Signal Denoising with Recurrent Spiking Neural Networks and Active Tuning.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2021, 2021

Latent Event-Predictive Encodings through Counterfactual Regularization.

[BibT_eX]

[DOI]

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

Demand Forecasting Using Ensemble Learning for Effective Scheduling of Logistic Orders.

[BibT_eX]

[DOI]

Proceedings of the Advances in Artificial Intelligence, Software and Systems Engineering, 2021

2020

Active Tuning.

[BibT_eX]

[DOI]

Matthias Karlbauer

CoRR, 2020

Hidden Latent State Inference in a Spatio-Temporal Generative Model.

[BibT_eX]

[DOI]

CoRR, 2020

Learning Precise Spike Timings with Eligibility Traces.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Inferring, Predicting, and Denoising Causal Wave Dynamics.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Fostering Event Compression Using Gated Surprise.

[BibT_eX]

[DOI]

Dania Humaidan

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Investigating Efficient Learning and Compositionality in Generative LSTM Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction.

[BibT_eX]

[DOI]

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Sequence Classification using Ensembles of Recurrent Generative Expert Modules.

[BibT_eX]

[DOI]

Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019

Learning, planning, and control in a monolithic neural event inference architecture.

[BibT_eX]

[DOI]

Neural Networks, 2019

Incorporating Adaptive RNN-Based Action Inference and Sensory Perception.

[BibT_eX]

[DOI]

Jakob Stoll

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Text and Time Series, 2019

Gradient-Based Learning of Compositional Dynamics with Modular RNNs.

[BibT_eX]

[DOI]

Patricia Rubisch

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

Inferring Event-Predictive Goal-Directed Object Manipulations in REPRISE.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

2018

Robust Real-Time 3D Person Detection for Indoor and Outdoor Applications.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Integrative Collision Avoidance Within RNN-Driven Many-Joint Robot Arms.

[BibT_eX]

[DOI]

Lea Hofmaier

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Online Carry Mode Detection for Mobile Devices with Compact RNNs.

[BibT_eX]

[DOI]

Philipp Kuhlmann

Paul Sanzenbacher

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Configuration Depending Crosstalk Torque Calibration for Robotic Manipulators with Deep Neural Regression Models.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Autonomous Systems 15, 2018

REPRISE: A Retrospective and Prospective Inference Scheme.

[BibT_eX]

[DOI]

Proceedings of the 40th Annual Meeting of the Cognitive Science Society, 2018

2017

Recurrent Neural Networks for Sequential Pattern Recognition Applications.

[BibT_eX]

[DOI]

PhD thesis, 2017

Inherently Constraint-Aware Control of Many-Joint Robot Arms with Inverse Recurrent Models.

[BibT_eX]

[DOI]

Adrian Zwiener

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

Inferring Adaptive Goal-Directed Behavior Within Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

Anticipatory Active Inference from Learned Recurrent Neural Forward Models.

[BibT_eX]

[DOI]

Theresa Schmitt

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

A Computational Model for the Dynamical Learning of Event Taxonomies.

[BibT_eX]

[DOI]

Christian Gumbsch

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

2016

Optimizing recurrent reservoirs with neuro-evolution.

[BibT_eX]

[DOI]

Neurocomputing, 2016

Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Inverse Recurrent Models - An Application Scenario for Many-Joint Robot Arm Control.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Revisiting Deep Convolutional Neural Networks for RGB-D Based Object Recognition.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Investigating Recurrent Neural Networks for Feature-Less Computational Drug Design.

[BibT_eX]

[DOI]

Alexander Dörr

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Vector-AMCL: Vector Based Adaptive Monte Carlo Localization for Indoor Maps.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Autonomous Systems 14, 2016

2015

An analysis of Dynamic Cortex Memory networks.

[BibT_eX]

[DOI]

Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Robust Visual Terrain Classification with Recurrent Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Learning Recurrent Dynamics using Differential Evolution.

[BibT_eX]

[DOI]

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

Investigating Long Short-Term Memory Networks for Various Pattern Recognition Problems.

[BibT_eX]

[DOI]

Dirk Krechel

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2014

ANTSAC: A Generic RANSAC Variant Using Principles of Ant Colony Algorithms.

[BibT_eX]

[DOI]

Ulrich Schwanecke

Proceedings of the 22nd International Conference on Pattern Recognition, 2014

Dynamic Cortex Memory: Enhancing Recurrent Neural Networks for Gradient-Based Sequence Learning.

[BibT_eX]

[DOI]

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

2013

OCT A-Scan based lung tumor tissue classification with Bidirectional Long Short Term Memory networks.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2013

Investigating Long Short-Term Memory Networks for various Pattern Recognition Prolems.

[BibT_eX]

Dirk Krechel

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2013

JANNLab Neural Network Framework for Java.

[BibT_eX]

Dirk Krechel