Hyperbolic Neural Networks for Molecular Generation. - Eric Qu; Dongmian Zou (CoRR, 2022)

Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer. - Eric Qu; Xufang Luo; Dongsheng Li 002 (ICLR, 2023)

Hyperbolic Convolution via Kernel Point Aggregation. - Eric Qu; Dongmian Zou (CoRR, 2023)

CNN Kernels Can Be the Best Shapelets. - Eric Qu; Yansen Wang; Xufang Luo; Wenqiang He; Kan Ren; Dongsheng Li 002 (ICLR, 2024)

Hyperbolic Kernel Convolution: A Generic Framework. - Eric Qu; Lige Zhang; Habib Debaya; Yue Wu; Dongmian Zou (LoG, 2024)

The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains. - Eric Qu; Aditi S. Krishnapriyan (NeurIPS, 2024)

Autoencoding Hyperbolic Representation for Adversarial Generation. - Eric Qu; Dongmian Zou (Trans. Mach. Learn. Res., 2024)