654 citations · 1.9k across the 149 of their papers we have counts for
15 papers · 1 filter
Over-the-Air Federated Learning in Heterogeneous Mobile Wireless Networks
Ming Xiang, Nicolò Michelusi, Yonina C. Eldar +1
Over-the-air computation has emerged as a scalable and efficient solution for deploying federated learning algorithms in wireless networks by exploiting waveform superposition for…
Learning to Replace MCMC in Split-Gibbs Diffusion Posterior Sampling via Deep Unfolding
Yi Zhang, Rui Guo, Mengchu Xu +2
Split Gibbs sampling enables diffusion posterior inference for general nonlinear inverse problems by decoupling prior and likelihood computations, allowing a pretrained diffusion p…
Neural Kalman Filtering for Unknown Dynamics: Task-Aware Learning with a Koopman Backbone
Mintaek Oh, Jeonghun Park, Nir Shlezinger +2
Recent years have witnessed a growing interest in AI-aided Kalman filters. While emerging methodologies, such as KalmanNet, were shown to facilitate tracking in partially known sta…
Toward Intelligent Skies: Signal Processing and AI Foundations of Low-Altitude Wireless Networks
Weijie Yuan, Geng Sun, Jiacheng Wang +7
The rapid growth of low-altitude aerial services and applications, driven by uncrewed aerial vehicles (UAVs), calls for a new class of digital infrastructure beyond conventional te…
Deflection-Optimal Spectral Design for Diagonal Screening in Sparse Phase Retrieval Initialization
Mengchu Xu, Yonina C. Eldar
Spectral initialization is a critical yet challenging step in sparse phase retrieval. Existing spectral design theory is largely tailored to dense phase retrieval, where the object…
Lattice Modulo Sampling
Yhonatan Kvich, Yonina C. Eldar
We propose a lattice-theoretic framework for modulo sampling of multidimensional bandlimited signals. Standard modulo analog-to-digital converters (ADCs) fold the signal component-…