Knowledge Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data Karpatne Anuj
Knowledge Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data Karpatne Anuj Given their tremendous success in commercial applications, machine learning (ML) models are…
Specifikacia Knowledge Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data Karpatne Anuj
Knowledge Guided Machine Learning: Accelerating Discovery Using Scientific Knowledge and Data Karpatne Anuj
Given their tremendous success in commercial applications, machine learning (ML) models are increasingly being considered as alternatives to science-based models in many disciplines. As a result, there is a growing interest in the scientific community on creating a new generation of methods that integrate scientific knowledge in ML frameworks. Yet, these black-box ML models have found limited success due to their inability to work well in the presence of limited training data and generalize to unseen scenarios.
Indeed, KGML involves diverse scientific and ML communities, where researchers and practitioners from various backgrounds and application domains are continually adding richness This emerging field, called scientific knowledge-guided ML (KGML), seeks a distinct departure from existing data-only or scientific knowledge-only methods to use knowledge and data at an equal footing.