Hybrid prediction

Building predictive models that are a hybrid of data driven statistical machine learning and domain knowledge.

Through Hybrid Prediction, we can reimagine existing approaches with new ones to create new opportunities and AI technologies for decision-making in real-time environments.

Hybrid Prediction focuses on including physical or theoretical constraints such as conservation of momentum, mass and energy into data driven models.

Hybrid Prediction can result in replacing components of biophysical models with data driven counterparts, using ML to make them run faster.

Hybrid Prediction is about incorporating everything we know or observe about a problem to generate predictions that are more efficient and more accurate.  We use a hybrid of solutions from Statistics and ML to achieve this.