受强制性开放获取政策约束的文章 - Guanchao Feng了解详情
无法在其他位置公开访问的文章：2 篇
Supervised and unsupervised learning of fetal heart rate tracings with deep Gaussian processes
G Feng, JG Quirk, PM Djurić
2018 14th Symposium on Neural Networks and Applications (NEUREL), 1-6, 2018
强制性开放获取政策： US National Institutes of Health
Fetal heart rate analysis with Gaussian processes
G Feng, J Gerald Quirk, C Heiselman, PM Djurić
Innovative Technologies and Signal Processing in Perinatal Medicine: Volume …, 2023
强制性开放获取政策： US National Institutes of Health
可在其他位置公开访问的文章：15 篇
Electrocorticography reveals thalamic control of cortical dynamics following traumatic brain injury
S Mofakham, A Fry, J Adachi, PL Stefancin, TQ Duong, JR Saadon, ...
Communications Biology 4 (1), 1210, 2021
强制性开放获取政策： US National Science Foundation
A differential measure of the strength of causation
K Butler, G Feng, PM Djurić
IEEE Signal Processing Letters 29, 2208-2212, 2022
强制性开放获取政策： US National Science Foundation, US Department of Education
On causal discovery with convergent cross mapping
K Butler, G Feng, PM Djurić
IEEE Transactions on Signal Processing 71, 2595-2607, 2023
强制性开放获取政策： US National Science Foundation, US Department of Education
Inference about causality from cardiotocography signals using Gaussian processes
G Feng, JG Quirk, PM Djurić
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
强制性开放获取政策： US National Science Foundation, US National Institutes of Health
Estimation of consecutively missed samples in fetal heart rate recordings
G Feng, JG Quirk, C Heiselman, PM Djurić
2020 28th European Signal Processing Conference (EUSIPCO), 1080-1084, 2021
强制性开放获取政策： US National Institutes of Health
Discovering causalities from cardiotocography signals using improved convergent cross mapping with Gaussian processes
G Feng, JG Quirk, PM Djurić
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
强制性开放获取政策： US National Institutes of Health
Detecting causality using deep gaussian processes
G Feng, JG Quirk, PM Djurić
2019 53rd Asilomar Conference on Signals, Systems, and Computers, 472-476, 2019
强制性开放获取政策： US National Institutes of Health
Exploiting Causality for Improved Prediction of Patient Volumes by Gaussian Processes
G Feng, K Yu, Y Wang, Y Yuan, PM Djuric
IEEE Journal of Biomedical and Health Informatics, 2021
强制性开放获取政策： US National Science Foundation
Extracting interpretable features for fetal heart rate recordings with Gaussian processes
G Feng, JG Quirk, PM Djurić
2019 IEEE 8th International Workshop on Computational Advances in Multi …, 2019
强制性开放获取政策： US National Institutes of Health
Cardiotocography analysis by empirical dynamic modeling and Gaussian processes
G Feng, C Heiselman, JG Quirk, PM Djurić
Frontiers in Bioengineering and Biotechnology 10, 1057807, 2023
强制性开放获取政策： US National Institutes of Health
Improving Phase-Rectified Signal Averaging for Fetal Heart Rate Analysis
T Chen, G Feng, C Heiselman, JG Quirk, PM Djurić
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
强制性开放获取政策： US National Institutes of Health
Predicting latent states of dynamical systems with state-space reconstruction and Gaussian processes
K Butler, G Feng, CB Mikell, S Mofakham, PM Djurić
2022 30th European Signal Processing Conference (EUSIPCO), 2216-2220, 2022
强制性开放获取政策： US National Science Foundation, US Department of Education
RF-based analytics generated by tag-to-tag networks
M Stanaćević, Y Karimi, G Feng, J Ryoo, A Athalye, S Das, PM Djurić
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
强制性开放获取政策： US National Science Foundation
Fetal Heart Rate Analysis from a Multi-task Learning Perspective with Gaussian Processes
T Chen, G Feng, C Heiselman, JG Quirk, PM Djuric
2023 31st European Signal Processing Conference (EUSIPCO), 1155-1159, 2023
强制性开放获取政策： US National Institutes of Health
Characterizing Fetal Heart Rate From A State Space Perspective
T Chen, G Feng, C Heiselman, JG Quirk, PM Djurić
2022 30th European Signal Processing Conference (EUSIPCO), 1248-1252, 2022
强制性开放获取政策： US National Institutes of Health
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