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Found 6 papers, 4 papers with code
Variational quantization for state space models
The main challenge is to model a rich variety of time series, leverage any available external signals and provide sharp predictions with statistical guarantees.
HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time series
Secondly, to leverage such a dataset, we propose a new hybrid forecasting model.
Extending the WILDS Benchmark for Unsupervised Adaptation
Unlabeled data can be a powerful point of leverage for mitigating these distribution shifts, as it is frequently much more available than labeled data and can often be obtained from distributions beyond the source distribution as well.
Global Wheat Head Dataset 2021: more diversity to improve the benchmarking of wheat head localization methods
We now release a new version of the Global Wheat Head Detection (GWHD) dataset in 2021, which is bigger, more diverse, and less noisy than the 2020 version.
Global Wheat Challenge 2020: Analysis of the competition design and winning models
Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems.
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Distribution shifts -- where the training distribution differs from the test distribution -- can substantially degrade the accuracy of machine learning (ML) systems deployed in the wild.
