A Scalable Probabilistic Model Selection Method for Deep Learning in Gene-Protein Network Inference and Integration
a novel model selection method to automate choice of deep neural network architectures
a novel model selection method to automate choice of deep neural network architectures
Understanding the capabilities of the human visual system with respect to biomedical imaging and in extracting and utilizing tacit knowledge of domain experts
Development and validation of a computational system that is able to automatically identify deceptive intent during computer-mediated, face-to-face communication
Aggregate gene expressions with context-dependent topological structures of gene regulations to infer new relationships
Seek innovations in extracting, understanding, and fusing tacit human domain knowledge to advance image semantics interpretation in knowledge rich domains