252 citations · 751 across the 19 of their papers we have counts for
3 papers · 1 filter
Towards Automated Deep Learning: Efficient Joint Neural Architecture and Hyperparameter Search
Arber Zela, Aaron Klein, Stefan Falkner +1
While existing work on neural architecture search (NAS) tunes hyperparameters in a separate post-processing step, we demonstrate that architectural choices and other hyperparameter…
BOHB: Robust and Efficient Hyperparameter Optimization at Scale
Stefan Falkner, Aaron Klein, Frank Hutter
Modern deep learning methods are very sensitive to many hyperparameters, and, due to the long training times of state-of-the-art models, vanilla Bayesian hyperparameter optimizatio…
Uncertainty Estimates and Multi-Hypotheses Networks for Optical Flow
Eddy Ilg, Özgün Çiçek, Silvio Galesso +4
Optical flow estimation can be formulated as an end-to-end supervised learning problem, which yields estimates with a superior accuracy-runtime tradeoff compared to alternative met…