activity
20172022
most citedLearning with Known Operators reduces Maximum Training Error Bounds

147 citations · 213 across the 8 of their papers we have counts for

collaborators

8 papers

q-fin.ST2022★ 1 cited

Time Series Analysis in American Stock Market Recovering in Post COVID-19 Pandemic Period

Weilin Fu, Zhuoran Li, Yupeng Zhang +1

Every financial crisis has caused a dual shock to the global economy. The shortage of market liquidity, such as default in debt and bonds, has led to the spread of bankruptcies, su…

eess.IV2019

Analyzing an Imitation Learning Network for Fundus Image Registration Using a Divide-and-Conquer Approach

Siming Bayer, Xia Zhong, Weilin Fu +2

Comparison of microvascular circulation on fundoscopic images is a non-invasive clinical indication for the diagnosis and monitoring of diseases, such as diabetes and hypertensions…

eess.IV2019★ 2 cited

What Do We Really Need? Degenerating U-Net on Retinal Vessel Segmentation

Weilin Fu, Katharina Breininger, Zhaoya Pan +1

Retinal vessel segmentation is an essential step for fundus image analysis. With the recent advances of deep learning technologies, many convolutional neural networks have been app…

eess.IV2019★ 1 cited

Lesson Learnt: Modularization of Deep Networks Allow Cross-Modality Reuse

Weilin Fu, Lennart Husvogt, Stefan Ploner James G. Fujimoto Andreas Maier

Fundus photography and Optical Coherence Tomography Angiography (OCT-A) are two commonly used modalities in ophthalmic imaging. With the development of deep learning algorithms, fu…

stat.ME2019★ 48 cited

Bayesian Symbolic Regression

Ying Jin, Weilin Fu, Jian Kang +2

Interpretability is crucial for machine learning in many scenarios such as quantitative finance, banking, healthcare, etc. Symbolic regression (SR) is a classic interpretable machi…

cs.LG2019

A Divide-and-Conquer Approach towards Understanding Deep Networks

Weilin Fu, Katharina Breininger, Roman Schaffert +2

Deep neural networks have achieved tremendous success in various fields including medical image segmentation. However, they have long been criticized for being a black-box, in that…