13 citations · 14 across the 6 of their papers we have counts for
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cs.LG2020
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation
Sophie Burkhardt, Jannis Brugger, Nicolas Wagner +3
Most deep neural networks are considered to be black boxes, meaning their output is hard to interpret. In contrast, logical expressions are considered to be more comprehensible sin…
cs.CV2020
NeuralQAAD: An Efficient Differentiable Framework for High Resolution Point Cloud Compression
Nicolas Wagner, Ulrich Schwanecke
In this paper, we propose NeuralQAAD, a differentiable point cloud compression framework that is fast, robust to sampling, and applicable to high resolutions. Previous work that is…
cs.CV2020
Super-Selfish: Self-Supervised Learning on Images with PyTorch
Nicolas Wagner, Anirban Mukhopadhyay
Super-Selfish is an easy to use PyTorch framework for image-based self-supervised learning. Features can be learned with 13 algorithms that span from simple classification to more…