Deep-learning inversion: a next generation seismic velocity-model building method. - Fangshu Yang; Jianwei Ma (CoRR, 2019)

Quantitative reconstruction of defects in multi-layered bonded composites using fully convolutional network-based ultrasonic inversion. - Jing Rao; Fangshu Yang; Huadong Mo; Stefan Kollmannsberger; Ernst Rank (CoRR, 2021)

Revisit Geophysical Imaging in A New View of Physics-informed Generative Adversarial Learning. - Fangshu Yang; Jianwei Ma (CoRR, 2021)

Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging. - Fangshu Yang; Thanh-An Pham; Nathalie Brandenberg; Matthias P. Lütolf; Jianwei Ma; Michael Unser (IEEE Trans. Image Process., 2021)

Seismic Random Noise Attenuation via Self-Supervised Transfer Learning. - Huimin Sun; Fangshu Yang; Jianwei Ma (IEEE Geosci. Remote. Sens. Lett., 2022)

Full-Waveform Inversion Using a Learned Regularization. - Pengpeng Sun; Fangshu Yang; Hongxian Liang; Jianwei Ma (IEEE Trans. Geosci. Remote. Sens., 2023)

Wasserstein Distance-Based Full-Waveform Inversion With a Regularizer Powered by Learned Gradient. - Fangshu Yang; Jianwei Ma (IEEE Trans. Geosci. Remote. Sens., 2023)