Xingzhi Sun

According to our database, Xingzhi Sun authored at least 12 papers between 2022 and 2026.

Collaborative distances:

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

2026

MIOFlow 2.0: A unified framework for inferring cellular stochastic dynamics from single cell and spatial transcriptomics data.

Xingzhi Sun, João F. Rocha, Brett Phelan, Dhananjay Bhaskar, Guillaume Huguet, Yanlei Zhang, Daniel Sumner Magruder, Alexander Tong, Ke Xu, Oluwadamilola Fasina, Mark Gerstein, Guy Wolf, Natalia Ivanova, Christine L. Chaffer, Smita Krishnaswamy

CoRR, March, 2026

Dispersion Loss Counteracts Embedding Condensation and Improves Generalization in Small Language Models.

Chen Liu, Xingzhi Sun, Xi Xiao, Alexandre Van Tassel, Ke Xu, Kristof Reimann, Danqi Liao, Mark Gerstein, Tianyang Wang, Xiao Wang, Smita Krishnaswamy

CoRR, February, 2026

2025

RNAGenScape: Property-guided Optimization and Interpolation of mRNA Sequences with Manifold Langevin Dynamics.

Danqi Liao, Chen Liu, Xingzhi Sun, Dié Tang, Haochen Wang, Scott E. Youlten, Srikar Krishna Gopinath, Haejeong Lee, Ethan C. Strayer, Antonio J. Giraldez, Smita Krishnaswamy

CoRR, October, 2025

STAGED: A Multi-Agent Neural Network for Learning Cellular Interaction Dynamics.

João F. Rocha, Ke Xu, Xingzhi Sun, Ananya Krishna, Dhananjay Bhaskar, Blanche Mongeon, Morgan Craig, Mark Gerstein, Smita Krishnaswamy

Proceedings of the 20th Machine Learning in Computational Biology (MLCB), 2025

Principal Curvatures Estimation with Applications to Single Cell Data.

Yanlei Zhang, Lydia Mezrag, Xingzhi Sun, Charles Xu, Kincaid MacDonald, Dhananjay Bhaskar, Smita Krishnaswamy, Guy Wolf, Bastian Rieck

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics.

Xingzhi Sun, Charles Xu, João F. Rocha, Chen Liu, Benjamin Hollander-Bodie, Laney Goldman, Marcello DiStasio, Michael Perlmutter, Smita Krishnaswamy

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds.

Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds.

Xingzhi Sun, Danqi Liao, Kincaid MacDonald, Yanlei Zhang, Chen Liu, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim G. J. Rudner, Smita Krishnaswamy

CoRR, 2024

Bayesian Spectral Graph Denoising with Smoothness Prior.

Samuel Leone, Xingzhi Sun, Michael Perlmutter, Smita Krishnaswamy

Proceedings of the 58th Annual Conference on Information Sciences and Systems, 2024

2023

Bayesian Formulations for Graph Spectral Denoising.

Samuel Leone, Xingzhi Sun, Michael Perlmutter, Smita Krishnaswamy

CoRR, 2023

Graph topological property recovery with heat and wave dynamics-based features on graphs.

Dhananjay Bhaskar, Yanlei Zhang, Charles Xu, Xingzhi Sun, Oluwadamilola Fasina, Guy Wolf, Maximilian Nickel, Michael Perlmutter, Smita Krishnaswamy

CoRR, 2023

2022

pureGAM: Learning an Inherently Pure Additive Model.

Xingzhi Sun, Ziyu Wang, Rui Ding, Shi Han, Dongmei Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022