Research Summary

Publications

Ningyuan (Teresa) Huang, Ron Levie, Soledad Villar (2023). Approximately Equivariant Graph Networks.

Jan Böker, Ron Levie, Ningyuan (Teresa) Huang, Soledad Villar, Christopher Morris (2023). Fine-grained Expressivity of Graph Neural Networks.

Ningyuan (Teresa) Huang, Soledad Villar, Carey E. Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman (2022). From Local to Global: Spectral-Inspired Graph Neural Networks . NeurIPS 2022 GLFrontiers Workshop.

Carey E. Priebe, Ningyuan (Teresa) Huang, Soledad Villar, Cong Mu, Li Chen (2022). Deep Learning is Provably Robust to Symmetric Label Noise.

Ningyuan (Teresa) Huang, David W. Hogg, Soledad Villar (2022). Dimensionality reduction, regularization, and generalization in overparameterized regressions. SIMODS.

Li Chen, Ningyuan (Teresa) Huang, Cong Mu, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe (2022). Deep Learning with Label Noise: A Hierarchical Approach.

Carey E. Priebe, Cencheng Shen, Ningyuan (Teresa) Huang, Tianyi Chen (2021). A Simple Spectral Failure Mode for Graph Convolutional Networks. TPAMI.

Ningyuan (Teresa) Huang, Pinki Mondal, Benjamin I. Cook, Sonali McDermid (2021). Moisture and temperature influences on nonlinear vegetation trends in Serengeti National Park. ERL.

(2020). Learning Robust Multimodal Knowledge Graph Representations.

(2019). Adversarial attacks against linear and deep-learning regressions in astronomy.

Code Dataset Poster