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Tensor Decompositions for Modeling Inverse Dynamics
Stephan Baier, Volker Tresp
Modeling inverse dynamics is crucial for accurate feedforward robot control. The model computes the necessary joint torques, to perform a desired movement. The highly non-linear in…
Attention-based Information Fusion using Multi-Encoder-Decoder Recurrent Neural Networks
Stephan Baier, Sigurd Spieckermann, Volker Tresp
With the rising number of interconnected devices and sensors, modeling distributed sensor networks is of increasing interest. Recurrent neural networks (RNN) are considered particu…
The Tensor Memory Hypothesis
Volker Tresp, Yunpu Ma
We discuss memory models which are based on tensor decompositions using latent representations of entities and events. We show how episodic memory and semantic memory can be realiz…
Tensor-Train Recurrent Neural Networks for Video Classification
Yinchong Yang, Denis Krompass, Volker Tresp
The Recurrent Neural Networks and their variants have shown promising performances in sequence modeling tasks such as Natural Language Processing. These models, however, turn out t…