Sidi Wu

Orcid: 0000-0003-1669-6690

According to our database1, Sidi Wu authored at least 16 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Functional autoencoder for smoothing and representation learning.
Stat. Comput., December, 2024

Error Analysis Based on Inverse Modified Differential Equations for Discovery of Dynamics Using Linear Multistep Methods and Deep Learning.
SIAM J. Numer. Anal., 2024

Solving parametric elliptic interface problems via interfaced operator network.
J. Comput. Phys., 2024

An Efficient System for Automatic Map Storytelling - A Case Study on Historical Maps.
CoRR, 2024

A roadmap for generative mapping: unlocking the power of generative AI for map-making.
CoRR, 2024

Fine-Tuning DeepONets to Enhance Physics-informed Neural Networks for solving Partial Differential Equations.
CoRR, 2024

A Physics-driven GraphSAGE Method for Physical Process Simulations Described by Partial Differential Equations.
CoRR, 2024

StegoGAN: Leveraging Steganography for Non-Bijective Image-to-Image Translation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Neuroimaging feature extraction using a neural network classifier for imaging genetics.
BMC Bioinform., December, 2023

Neural networks for scalar input and functional output.
Stat. Comput., October, 2023

Cross-attention Spatio-temporal Context Transformer for Semantic Segmentation of Historical Maps.
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, 2023

2022
INN: Interfaced neural networks as an accessible meshless approach for solving interface PDE problems.
J. Comput. Phys., 2022

On convergence of neural network methods for solving elliptic interface problems.
CoRR, 2022

Unsupervised historical map registration by a deformation neural network.
Proceedings of the 5th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery, 2022

2020
FuncNN: An R Package to Fit Deep Neural Networks Using Generalized Input Spaces.
CoRR, 2020

Derivation of Geometrically and Semantically Annotated UAV Datasets at Large Scales from 3D City Models.
Proceedings of the 25th International Conference on Pattern Recognition, 2020


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