malteschilling

AdvancedML

Course on advanced Machine Learning. (html) Slides for the lecture.

advml_binder

arob_notebooks

cognitiveWalker

Cognitive system for the control of a hexapod robot.

ddrl

Deep Decentralized Reinforcement Learning - locally structured architecture for DRL in a continuous locomotion control task.

ddrl_hexapod

drl_seminar

Deep Reinforcement Learning Course 2017 - includes basic python implementations of (deep) reinforcement learning algorithm.

hector

ODE Simulation and Visualization of the six-legged Hector robot.

hierarchicalQuaternionMMC

Implementation of a hierarchical Mean of Multiple Computation neural network in Python. The body model is based on an axis-angle representation of joint movements using dual quaternions. It is shown in detail how the network provides a solution for the forward kinematic problem applied for the case of a seven degrees of freedom robot manipulator. Furthermore, it is used in a complex scenario of a bimanual movement task. This demonstrates how the MMC approach can be easily scaled up from a representation of a single arm to a complex model of a complete body.

temporalConvolutionalNetwork

Implementation of a Temporal Convolutional Network in Keras - it is tested on a classification and regression task.

malteschilling/ddrl_hexapod

malteschilling/ddrl

Deep Decentralized Reinforcement Learning - locally structured architecture for DRL in a continuous locomotion control task.

malteschilling/temporalConvolutionalNetwork

Implementation of a Temporal Convolutional Network in Keras - it is tested on a classification and regression task.

malteschilling/hierarchicalQuaternionMMC

Implementation of a hierarchical Mean of Multiple Computation neural network in Python. The body model is based on an axis-angle representation of joint movements using dual quaternions. It is shown in detail how the network provides a solution for the forward kinematic problem applied for the case of a seven degrees of freedom robot manipulator. Furthermore, it is used in a complex scenario of a bimanual movement task. This demonstrates how the MMC approach can be easily scaled up from a representation of a single arm to a complex model of a complete body.

malteschilling/AdvancedML

Course on advanced Machine Learning. (html) Slides for the lecture.

malteschilling/advml_binder

malteschilling/arob_notebooks

malteschilling/cognitiveWalker

Cognitive system for the control of a hexapod robot.

malteschilling/drl_seminar

Deep Reinforcement Learning Course 2017 - includes basic python implementations of (deep) reinforcement learning algorithm.

malteschilling/hector

ODE Simulation and Visualization of the six-legged Hector robot.

malteschilling/pipe_project

malteschilling/joint_mappings_nn

Learning of a mapping between different legs - given as joint angles from one (target) leg and corresponding joint angles for the posterior leg (aiming at this position).

malteschilling/LearningPredictiveEncoderDecoder

Learning Predictive Encoder-Decoder for falling Object images.

malteschilling/Lehrprobe_MS_AnalyseErwarteterFall

malteschilling/logseq

This is simply to publish my templates to the world :)

malteschilling/malteschilling.github.io

malteschilling/normalizationMMC

Implementation of a functional internal body model that is based on the Mean of Multiple Computation principle in Python. The model is completely realized in a recurrent neural network as necessary normalization steps are integrated into the neural model itself. Furthermore, a dynamic extension is applied to the model.

malteschilling/PIPECore

Core libraries for building and editing Petri nets

malteschilling/pyESN

Echo State Networks in Python

malteschilling/robust_ddrl

Experiments on Robustness of Decentralized DRL approach wrt. variation of hyper parameters of Neural Networks.