most citedCUTS: Neural Causal Discovery from Irregular Time-Series Data

9 citations · 29 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2023

SHoP: A Deep Learning Framework for Solving High-order Partial Differential Equations

Tingxiong Xiao, Runzhao Yang, Yuxiao Cheng +2

Solving partial differential equations (PDEs) has been a fundamental problem in computational science and of wide applications for both scientific and engineering research. Due to…

cs.LG2023★ 3 cited

CUTS+: High-dimensional Causal Discovery from Irregular Time-series

Yuxiao Cheng, Lianglong Li, Tingxiong Xiao +4

Causal discovery in time-series is a fundamental problem in the machine learning community, enabling causal reasoning and decision-making in complex scenarios. Recently, researcher…

cs.LG2023★ 9 cited

CUTS: Neural Causal Discovery from Irregular Time-Series Data

Yuxiao Cheng, Runzhao Yang, Tingxiong Xiao +4

Causal discovery from time-series data has been a central task in machine learning. Recently, Granger causality inference is gaining momentum due to its good explainability and hig…

cs.CV2023★ 2 cited

DarkVision: A Benchmark for Low-light Image/Video Perception

Bo Zhang, Yuchen Guo, Runzhao Yang +4

Imaging and perception in photon-limited scenarios is necessary for various applications, e.g., night surveillance or photography, high-speed photography, and autonomous driving. I…

eess.SP2022★ 2 cited

EEG Opto-processor: epileptic seizure detection using diffractive photonic computing units

Tao Yan, Maoqi Zhang, Sen Wan +5

Electroencephalography (EEG) analysis extracts critical information from brain signals, which has provided fundamental support for various applications, including brain-disease dia…

cs.LG2022★ 8 cited

Optical Neural Ordinary Differential Equations

Yun Zhao, Hang Chen, Min Lin +5

Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance. However, the successively cascading of network hidden layers r…

eess.IV2022★ 1 cited

SCI: A Spectrum Concentrated Implicit Neural Compression for Biomedical Data

Runzhao Yang, Tingxiong Xiao, Yuxiao Cheng +4

Massive collection and explosive growth of biomedical data, demands effective compression for efficient storage, transmission and sharing. Readily available visual data compression…

cs.ET2022★ 1 cited

All-optical graph representation learning using integrated diffractive photonic computing units

Tao Yan, Rui Yang, Ziyang Zheng +3

Photonic neural networks perform brain-inspired computations using photons instead of electrons that can achieve substantially improved computing performance. However, existing arc…

physics.optics2022★ 3 cited

Photonic unsupervised learning processor for secure and high-throughput optical fiber communication

Yitong Chen, Tiankuang Zhou, Jiamin Wu +4

Following the explosive growth of global data, there is an ever-increasing demand for high-throughput optical fiber communication (OFC) systems to perform massive data transmission…