158 citations · 240 across the 9 of their papers we have counts for
4 papers · 1 filter
Explainability-aided Domain Generalization for Image Classification
Robin M. Schmidt
Traditionally, for most machine learning settings, gaining some degree of explainability that tries to give users more insights into how and why the network arrives at its predicti…
Collaborative Filtering under Model Uncertainty
Robin M. Schmidt, Moritz Hahn
In their work, Dean, Rich, and Recht create a model to research recourse and availability of items in a recommender system. We used the definition of predictive multiplicity by Mar…
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers
Robin M. Schmidt, Frank Schneider, Philipp Hennig
Choosing the optimizer is considered to be among the most crucial design decisions in deep learning, and it is not an easy one. The growing literature now lists hundreds of optimiz…
Recurrent Neural Networks (RNNs): A gentle Introduction and Overview
Robin M. Schmidt
State-of-the-art solutions in the areas of "Language Modelling & Generating Text", "Speech Recognition", "Generating Image Descriptions" or "Video Tagging" have been using Recurren…