3 papers
eess.SP2026
Total Variation Sparse Bayesian Learning for Block Sparsity via Majorization-Minimization
Yanbin He, Geethu Joseph
Block sparsity is a widely exploited structure in sparse recovery, offering significant gains when signal blocks are known. Yet, practical signals often exhibit unknown block bound…
cs.LG2025
Assessing the Geographic Generalization and Physical Consistency of Generative Models for Climate Downscaling
Carlo Saccardi, Maximilian Pierzyna, Haitz Sáez de Ocáriz Borde +6
Kilometer-scale weather data is crucial for real-world applications but remains computationally intensive to produce using traditional weather simulations. An emerging solution is…
eess.SP2024
Efficient Off-Grid Bayesian Parameter Estimation for Kronecker-Structured Signals
Yanbin He, Geethu Joseph
This work studies the problem of jointly estimating unknown parameters from Kronecker-structured multidimensional signals, which arises in applications like intelligent reflecting…