Sibo Cheng

发表

Error covariance tuning in variational data assimilation: application to an operating hydrological model

Jean-Philippe Argaud, Angélique Ponçot, Bertrand Iooss, 2020, Stochastic Environmental Research and Risk Assessment.

Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting

Yufang Jin, I. Prentice, R. Arcucci, 2022, Journal of Computational Physics.

An Efficient Digital Twin Based on Machine Learning Svd Autoencoder and Generalised Latent Assimilation for Nuclear Reactor Physics

R. Arcucci, Dunhui Xiao, Helin Gong, 2022, SSRN Electronic Journal.

Reduced-order digital twin and latent data assimilation for global wildfire prediction

R. Arcucci, M. Kasoar, Sibo Cheng, 2023, Natural Hazards and Earth System Sciences.

Parameter Flexible Wildfire Prediction Using Machine Learning Techniques: Forward and Inverse Modelling

Yufang Jin, I. Prentice, S. Harrison, 2022, Remote. Sens..

Optimal vaccination strategies for COVID-19 based on dynamical social networks with real-time updating

C. Pain, R. Arcucci, Yi-Ke Guo, 2021, medRxiv.

Real-time updating of dynamic social networks for COVID-19 vaccination strategies

Rossella Arcucci, Sibo Cheng, Christopher C. Pain, 2021, Journal of ambient intelligence and humanized computing.

A Graph Clustering Approach to Localization for Adaptive Covariance Tuning in Data Assimilation Based on State-Observation Mapping

Jean-Philippe Argaud, Angélique Ponçot, Bertrand Iooss, 2020, Mathematical Geosciences.

Observation data compression for variational assimilation of dynamical systems

Jean-Philippe Argaud, Didier Lucor, Sibo Cheng, 2021, J. Comput. Sci..

Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review

A. Carrassi, M. Bocquet, Ronan Fablet, 2023, IEEE/CAA Journal of Automatica Sinica.

Ensemble latent assimilation with deep learning surrogate model: application to drop interaction in a microfluidics device.

Nam-Trung Nguyen, Shu Beng Tor, Say Hwa Tan, 2022, Lab on a chip.

Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models

C. Pain, O. Matar, P. Angeli, 2022, Journal of Scientific Computing.

Generative Text-Guided 3D Vision-Language Pretraining for Unified Medical Image Segmentation

Zhiwei Xiong, R. Arcucci, Che Liu, 2023, ArXiv.

Spectral Cross-Domain Neural Network with Soft-adaptive Threshold Spectral Enhancement

R. Arcucci, Weiping Ding, Sibo Cheng, 2023, ArXiv.

Error covariance tuning in variational data assimilation: application to an operating hydrological model

B. Iooss, D. Lucor, Sibo Cheng, 2020, Stochastic Environmental Research and Risk Assessment.

Background error covariance iterative updating with invariant observation measures for data assimilation

Jean-Philippe Argaud, Angélique Ponçot, Bertrand Iooss, 2019, Stochastic Environmental Research and Risk Assessment.

Optimization of microfluidic synthesis of silver nanoparticles: a generic approach using machine learning

N. Kovalchuk, M. Simmons, R. Arcucci, 2023, Chemical Engineering Research and Design.

Data-Enabled Physics-Informed Machine Learning for Reduced-Order Modeling Digital Twin: Application to Nuclear Reactor Physics

Helin Gong, Sibo Cheng, Zhang Chen, 2022, Nuclear Science and Engineering.

Frozen Language Model Helps ECG Zero-Shot Learning

Jun Yu Li, R. Arcucci, Che Liu, 2023, MIDL.

Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias

Lei Ma, R. Arcucci, Mi Zhang, 2023, ArXiv.

Hierarchical Bayesian nearest neighbor co-kriging Gaussian process models; an application to intersatellite calibration

Georgios Karagiannis, Emily L. Kang, Bledar A. Konomi, 2020, 2004.01341.

Accurate identification and measurement of the precipitate area by two-stage deep neural networks in novel chromium-based alloys.

R. Arcucci, Dunhui Xiao, A. J. Knowles, 2023, Physical Chemistry, Chemical Physics - PCCP.

Analyzing drop coalescence in microfluidic device with a deep learning generative model

M. Simmons, O. Matar, R. Arcucci, 2023, Physical chemistry chemical physics : PCCP.

Computational fluid dynamics simulations of phase separation in dispersed oil-water pipe flows

O. Matar, P. Angeli, R. Arcucci, 2023, Chemical Engineering Science.

Computational ﬂuid dynamics simulations of phase separation in dispersed oil-water pipe ﬂows

O. Matar, P. Angeli, R. Arcucci, 2022 .

Observation error covariance specification in dynamical systems for data assimilation using recurrent neural networks pdf

Sibo Cheng, Mingming Qiu, Sibo Cheng, 2021, Neural Computing and Applications.

Ensemble latent assimilation with deep learning surrogate model: application to drop interaction in a microfluidics device.

O. Matar, Yi-Ke Guo, Sibo Cheng, 2022, Lab on a chip.

IMITATE: Clinical Prior Guided Hierarchical Vision-Language Pre-training

Sibo Cheng, Che Liu, Rossella Arcucci, 2023, ArXiv.

M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization

Chen Chen, Wenjia Bai, Weitong Zhang, 2023, MICCAI.

Med-UniC: Unifying Cross-Lingual Medical Vision-Language Pre-Training by Diminishing Bias

Lei Ma, Mi Zhang, Benyou Wang, 2023, NeurIPS.

M-FLAG: Medical Vision-Language Pre-training with Frozen Language Models and Latent Space Geometry Optimization

Chen Chen, Wenjia Bai, Weitong Zhang, 2023, MICCAI.

A Generative Model for Surrogates of Spatial-Temporal Wildfire Nowcasting

Sibo Cheng, Yike Guo, Rossella Arcucci, 2023, IEEE Transactions on Emerging Topics in Computational Intelligence.

Data-driven surrogate model with latent data assimilation: Application to wildfire forecasting

Yufang Jin, I. Prentice, Yi-Ke Guo, 2022, J. Comput. Phys..

ETP: Learning Transferable ECG Representations via ECG-Text Pre-training

Mi Zhang, Che Liu, Sibo Cheng, 2023, ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Explainable Global Wildfire Prediction Models using Graph Neural Networks

M. Kasoar, Sibo Cheng, Rossella Arcucci, 2024, ArXiv.

Liquid–Liquid Dispersion Performance Prediction and Uncertainty Quantification Using Recurrent Neural Networks

D. Juric, Seungwon Shin, J. Chergui, 2024, Industrial & engineering chemistry research.

Reduced Order Surrogate Modelling and Latent Assimilation for Dynamical Systems

Sibo Cheng, C. Q. Casas, Rossella Arcucci, 2022, ICCS.

Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale

Sibo Cheng, Rossella Arcucci, Hector Chassagnon, 2024, IEEE Transactions on Emerging Topics in Computational Intelligence.