Ningyuan Huang

According to our database, Ningyuan Huang authored at least 18 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

CosmoBench: A Multiscale, Multiview, Multitask Cosmology Benchmark for Geometric Deep Learning.

Ningyuan Huang, Richard Stiskalek, Jun-Young Lee, Adrian E. Bayer, Charles C. Margossian, Christian Kragh Jespersen, Lucia A. Perez, Lawrence K. Saul, Francisco Villaescusa-Navarro

CoRR, July, 2025

Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity.

Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil, Pau Rodríguez, Luca Zappella, Federico Danieli

CoRR, June, 2025

CAO-RONet: A Robust 4D Radar Odometry with Exploring More Information from Low-Quality Points.

Zhiheng Li, Yubo Cui, Ningyuan Huang, Chenglin Pang, Zheng Fang

CoRR, March, 2025

2024

An EEG abnormality detection algorithm based on graphic attention network.

Junwei Duan, Fei Xie, Ningyuan Huang, Ningdi Luo, Ziyu Guan, Wei Zhao, Gang Gao

Multim. Tools Appl., February, 2024

Learning functions on symmetric matrices and point clouds via lightweight invariant features.

Ben Blum-Smith, Ningyuan Huang, Marco Cuturi, Soledad Villar

CoRR, 2024

A Spectral Analysis of Graph Neural Networks on Dense and Sparse Graphs.

Luana Ruiz, Ningyuan Teresa Huang, Soledad Villar

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Approximately Equivariant Graph Networks.

Ningyuan Huang, Ron Levie, Soledad Villar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fine-grained Expressivity of Graph Neural Networks.

Jan Böker, Ron Levie, Ningyuan Huang, Soledad Villar, Christopher Morris

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Prospective Learning: Principled Extrapolation to the Future.

Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael L. Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam S. Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions.

Ningyuan Teresa Huang, David W. Hogg, Soledad Villar

SIAM J. Math. Data Sci., 2022

A Simple Spectral Failure Mode for Graph Convolutional Networks.

Carey E. Priebe, Cencheng Shen, Ningyuan Huang, Tianyi Chen

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Graph Neural Networks for Community Detection on Sparse Graphs.

Luana Ruiz, Ningyuan Huang, Soledad Villar

CoRR, 2022

Deep Learning is Provably Robust to Symmetric Label Noise.

Carey E. Priebe, Ningyuan Huang, Soledad Villar, Cong Mu, Li Chen

CoRR, 2022

From Local to Global: Spectral-Inspired Graph Neural Networks.

Ningyuan Huang, Soledad Villar, Carey E. Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman

CoRR, 2022

Endowing Language Models with Multimodal Knowledge Graph Representations.

Ningyuan Huang, Yash R. Deshpande, Yibo Liu, Houda Alberts, Kyunghyun Cho, Clara Vania, Iacer Calixto

CoRR, 2022

Deep Learning with Label Noise: A Hierarchical Approach.

Li Chen, Ningyuan Huang, Cong Mu, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe

CoRR, 2022

Prospective Learning: Back to the Future.

Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam S. Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang

CoRR, 2022

2021

A Short Tutorial on The Weisfeiler-Lehman Test And Its Variants.

Ningyuan Teresa Huang, Soledad Villar

Proceedings of the IEEE International Conference on Acoustics, 2021