TeamCurrent

Reserch Title:
Array Processing with Riemannian Geometry

Reserch Title:
Riemannian Geometry and Manifold Analysis in Reinforcement Learning, Signal Processing, and Optimization

Reserch Title:
Hyperbolic Geometry in Machine Learning

Reserch Title:
Multi-Graph Signal Processing

Reserch Title:
Novel methods for measurement and data-driven analysis of acoustic and magnetic emissions

Reserch Title:
Geometric Methods with Applications to Feature Selection and Individual Treatment Effect

Reserch Title:
Time-frequency Representation Using the Geometry of Time-delay Embedding

Reserch Title:
Holomorphic Interpolation Schemes for Multimodal Manifold Learning

Reserch Title:
Optimal Domain Adaptation on Riemannian Manifolds using Procrustes Analysis

Reserch Title:
Scalable Sensor Fusion via a Reference Subset

Reserch Title:
Sparse dictionary learning optimized for behavior prediction: an integrated framework for learning sparse neuronal events encoding behavior