On the Compatibility between a Neural Network and a Partial Differential Equation for Physics-informed Learning. - Kuangdai Leng; Jeyan Thiyagalingam (CoRR, 2022)

Padding-Free Convolution Based on Preservation of Differential Characteristics of Kernels. - Kuangdai Leng; Jeyan Thiyagalingam (ICMLA, 2023)

Unsupervised Few-Shot Image Segmentation with Dense Feature Learning and Sparse Clustering. - Kuangdai Leng; Robert Atwood; Winfried Kockelmann; Deniza Chekrygina; Jeyan Thiyagalingam (VISIGRAPP (2): VISAPP, 2024)

GlobalTomo: A global dataset for physics-ML seismic wavefield modeling and FWI. - Shiqian Li; Zhi Li; Zhancun Mu; Shiji Xin; Zhixiang Dai; Kuangdai Leng; Ruihua Zhang; Xiaodong Song; Yixin Zhu (CoRR, 2024)

Deep Learning Evidence for Global Optimality of Gerver's Sofa. - Kuangdai Leng; Jia Bi; Jaehoon Cha; Samuel Pinilla; Jeyan Thiyagalingam (CoRR, 2024)

Zero coordinate shift: Whetted automatic differentiation for physics-informed operator learning. - Kuangdai Leng; Mallikarjun Shankar; Jeyan Thiyagalingam (J. Comput. Phys., 2024)