Graph-Structured Kernel Design for Power Flow Learning using Gaussian Processes
This paper presents a physics-inspired graph-structured kernel designed for power flow
learning using Gaussian Process (GP). The kernel, named the vertex-degree kernel (VDK) …
learning using Gaussian Process (GP). The kernel, named the vertex-degree kernel (VDK) …
Ensembles of Informative Representations for Self-Supervised Learning
The requirement of large-size labeled training datasets often prohibits the deployment of
supervised learning models in several applications with high acquisition costs and privacy …
supervised learning models in several applications with high acquisition costs and privacy …
Gaussian Process-based Active Learning for Efficient Cardiovascular Disease Inference
Cardiovascular disease (CVD) poses a significant global health challenge, and accurate
inference methods are vital for early detection and intervention. However, the quality of …
inference methods are vital for early detection and intervention. However, the quality of …
Simpler Yet Smarter AI: Learn and Optimize With Just a Few Labeled Data
K Polyzos - 2024 - search.proquest.com
Abstract Machine learning (ML) has gained popularity due to its well-documented merits in
several inference tasks across diverse applications including healthcare, robotics and …
several inference tasks across diverse applications including healthcare, robotics and …