8 papers
HarmoCore: Functional Latent Diffusion for Sparse Reconstruction of Oscillatory Wave Fields
Lihao Chen, Xinyu Zhang, Panqi Chen +4
Reconstructing oscillatory wave fields from scattered sensors is a severely underdetermined inverse problem. Beyond the challenges of general physical-field reconstruction, wave re…
TRACE: Retrospective Streaming Generation of Physical Fields under Sparse Structured Sensing
Xinyu Zhang, Lihao Chen, Panqi Chen +4
Reconstructing continuous physical fields from sparse measurements is central to scientific monitoring, inverse modeling, and digital-twin construction. Generative reconstruction h…
StreamPhy: Streaming Inference of High-Dimensional Physical Dynamics via State Space Models
Panqi Chen, Yifan Sun, Shikai Fang +2
Inferring the evolution of high-dimensional and multi-modal (e.g., spatio-temporal) physical fields from irregular sparse measurements in real time is a fundamental challenge in sc…
Deep Tensor Learning for Reliable Channel Charting from Incomplete and Noisy Measurements
Ge Chen, Panqi Chen, Lei Cheng
Channel charting has emerged as a powerful tool for user equipment localization and wireless environment sensing. Its efficacy lies in mapping high-dimensional channel data into lo…
FieldFormer: Self-supervised Reconstruction of Physical Fields via Tensor Attention Prior
Panqi Chen, Siyuan Li, Lei Cheng +3
Reconstructing physical field tensors from \textit{in situ} observations, such as radio maps and ocean sound speed fields, is crucial for enabling environment-aware decision making…
Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
Panqi Chen, Yifan Sun, Lei Cheng +6
Modeling and reconstructing multidimensional physical dynamics from sparse and off-grid observations presents a fundamental challenge in scientific research. Recently, diffusion-ba…
Functional Complexity-adaptive Temporal Tensor Decomposition
Panqi Chen, Lei Cheng, Jianlong Li +4
Tensor decomposition is a fundamental tool for analyzing multi-dimensional data by learning low-rank factors to represent high-order interactions. While recent works on temporal te…
Estimating Channels With Hundreds of Sub-Paths for MU-MIMO Uplink: A Structured High-Rank Tensor Approach
Panqi Chen, Lei Cheng
This letter introduces a structured high-rank tensor approach for estimating sub-6G uplink channels in multi-user multiple-input and multiple-output (MU-MIMO) systems. To tackle th…