Wai Hoh Tang

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	All	Since 2019
Citations	79	79
h-index	4	4
i10-index	2	2

202020212022202320244 13 24 28 9

Co-authors

Adrian RöllinNational University of SingaporeVerified email at nus.edu.sg
Thorsten Wohland National University of SingaporeVerified email at nus.edu.sg
Harikrushnan BalasubramanianResearch Specialist (Howard Hughes Medical Institute - Janelia Research Campus)Verified email at hhmi.org
Jagadish SankaranGenome Institute of SingaporeVerified email at gis.a-star.edu.sg
Xue Wen NgGraduate student, National University of SingaporeVerified email at u.nus.edu
Daniel AikNational University of SingaporeVerified email at u.nus.edu
Kenji KawaguchiPresidential Young Professor, National University of SingaporeVerified email at nus.edu.sg
Arno SolinAssistant Professor in Machine Learning, Aalto UniversityVerified email at aalto.fi
Sarthak MittalMila, Université de MontréalVerified email at umontreal.ca
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
Juho KannalaAssociate Professor, Aalto University, FinlandVerified email at aalto.fi
Vikas VermaAalto University/ MILA/ Google BrainVerified email at google.com
Yingtian ZouNational University of SingaporeVerified email at nus.edu.sg
Apostolos PsarosAI Research, Fidelity InvestmentsVerified email at fmr.com
Qianli ShenNational University of SingaporeVerified email at comp.nus.edu.sg
Zhun DengPostdoctoral Researcher, Columbia UniversityVerified email at columbia.edu

Wai Hoh Tang

Research Associate, Imperial College London

Verified email at imperial.ac.uk

Deep Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Simultaneous spatiotemporal super-resolution and multi-parametric fluorescence microscopy J Sankaran, H Balasubramanian, WH Tang, XW Ng, A Röllin, T Wohland Nature Communications 12 (1), 1748, 2021	38	2021
Model identification for ARMA time series through convolutional neural networks WH Tang, A Röllin Decision Support Systems 146, 113544, 2021	22	2021
Preparation of live cell samples for fluorescence spectroscopy and computational super-resolution imaging J Sankaran, H Balasubramanian, WH Tang, XW Ng, A Röllin, T Wohland	6	2021
Deep learning approaches for imaging fluorescence correlation spectroscopy parameter estimation with limited data sets T Wohland, WH Tang, SR Sim, D Aik, A Röllin Biophysical Journal 121 (3), 533a, 2022	4	2022
Mixupe: Understanding and improving mixup from directional derivative perspective Y Zou, V Verma, S Mittal, WH Tang, H Pham, J Kannala, Y Bengio, A Solin, ... Uncertainty in Artificial Intelligence, 2597-2607, 2023	3	2023
Simultaneous spatiotemporal computational super-resolution and multi-parametric fluorescence microscopy J Sankaran, H Balasubramanian, WH Tang, XW Ng, A Röllin, T Wohland	3	2021
Deep learning reduces data requirements and allows real-time measurements in Imaging FCS WH Tang, SR Sim, DYK Aik, AVS Nelanuthala, T Athilingam, A Röllin, ... Biophysical Journal, 2023	1	2023
Fluorescence Spectroscopy Analysis Through Convolutional Neural Networks WH Tang National University of Singapore, 2021	1*	2021
SRRF ‘n’TIRF-FCS: Simultaneous spatiotemporal super-resolution microscopy J Sankaran, H Balasubramanian, WH Tang, XW Ng, A Röllin, T Wohland bioRxiv, 2020.02. 26.965905, 2020	1	2020
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification Q Shen, WH Tang, Z Deng, A Psaros, K Kawaguchi Advances in Neural Information Processing Systems 36, 2024		2024
FCSNet and ImFCSNet, convolutional neural network approaches to FCS data analysis T Wohland, WH Tang, SR Sim, DY Aik, AVS Nelanuthala, A Röllin Biophysical Journal 122 (3), 429a, 2023		2023

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