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- Technical University of MunichDE30 papers
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5 papers · 2 filters
Visual Evaluation of Generative Adversarial Networks for Time Series Data
Hiba Arnout, Johannes Kehrer, Johanna Bronner +1
A crucial factor to trust Machine Learning (ML) algorithm decisions is a good representation of its application field by the training dataset. This is particularly true when parts…
Neural Network Memorization Dissection
Jindong Gu, Volker Tresp
Deep neural networks (DNNs) can easily fit a random labeling of the training data with zero training error. What is the difference between DNNs trained with random labels and the o…
BioNLP-OST 2019 RDoC Tasks: Multi-grain Neural Relevance Ranking Using Topics and Attention Based Query-Document-Sentence Interactions
Yatin Chaudhary, Pankaj Gupta, Hinrich Schütze
This paper presents our system details and results of participation in the RDoC Tasks of BioNLP-OST 2019. Research Domain Criteria (RDoC) construct is a multi-dimensional and broad…
Interpretable Dynamics Models for Data-Efficient Reinforcement Learning
Markus Kaiser, Clemens Otte, Thomas Runkler +1
In this paper, we present a Bayesian view on model-based reinforcement learning. We use expert knowledge to impose structure on the transition model and present an efficient learni…
Counterfactual Visual Explanations
Yash Goyal, Ziyan Wu, Jan Ernst +3
In this work, we develop a technique to produce counterfactual visual explanations. Given a 'query' image for which a vision system predicts class , a counterfactual visual…