Bayesian Active learning Anomaly detection.jl

Here we are using Bayesian CNNs to detect anomalies in time series data. We combine imporovements from different fields to produce one generalised active learning algorithm based on GASF, bayesian inference, deep image learning, batchBALD acquisition function.

Datasets

Here is a list of the several public industrial datasets on which we intend to benchmark out algorithm.

1. SECOM: Semiconductor manufacturing process data.
2. Data-driven prediction of battery cycle life before capacity degradation
3. PHM DATA Challenge 18: Etching tool fault detection (PdM)

Authors and Contributors

• Author: Devesh Jawla
• Contributors

Supporting and Citing

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