Image coding in compressed sensing based on noise shaping. - Li Li; Jiachen Yao; Na Deng (ISPACS, 2017)

Multi-Step-Ahead Tool State Monitoring Using Clustering Feature-Based Recurrent Fuzzy Neural Networks. - Jiachen Yao; Baochun Lu; Junli Zhang (IEEE Access, 2021)

On the Convergence of Optimizing Persistent-Homology-Based Losses. - Yikai Zhang 003; Jiachen Yao; Yusu Wang 001; Chao Chen 012 (CoRR, 2022)

Selecting Real-World Objects via User-Perspective Phone Occlusion. - Yue Qin; Chun Yu; Wentao Yao; Jiachen Yao; Chen Liang; Yueting Weng; Yukang Yan; Yuanchun Shi (CHI, 2023)

Learning to Segment from Noisy Annotations: A Spatial Correction Approach. - Jiachen Yao; Yikai Zhang 003; Songzhu Zheng; Mayank Goswami 001; Prateek Prasanna; Chao Chen 012 (ICLR, 2023)

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks. - Jiachen Yao; Chang Su; Zhongkai Hao; Songming Liu; Hang Su 006; Jun Zhu 001 (ICML, 2023)

Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images. - Shahira Abousamra; Danielle Fassler; Jiachen Yao; Rajarsi R. Gupta; Tahsin M. Kurç; Luisa F. Escobar-Hoyos; Dimitris Samaras; Kenneth Shroyer; Joel H. Saltz; Chao Chen 012 (MIDL, 2023)

Topological Analysis of Mouse Brain Vasculature via 3d Light-Sheet Microscopy Images. - Jiachen Yao; Nina Hagemann; Qiaojie Xiong; Jianxu Chen 001; Dirk M. Hermann; Chao Chen (ISBI, 2024)

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs. - Zhongkai Hao; Jiachen Yao; Chang Su; Hang Su 006; Ziao Wang; Fanzhi Lu; Zeyu Xia 003; Yichi Zhang; Songming Liu; Lu Lu; Jun Zhu 001 (NeurIPS, 2024)

Preconditioning for Physics-Informed Neural Networks. - Songming Liu; Chang Su; Jiachen Yao; Zhongkai Hao; Hang Su 006; Youjia Wu; Jun Zhu 001 (CoRR, 2024)

A Theoretical Study of Neural Network Expressive Power via Manifold Topology. - Jiachen Yao; Mayank Goswami 001; Chao Chen 012 (CoRR, 2024)

Adversarial Vessel-Unveiling Semi-Supervised Segmentation for Retinopathy of Prematurity Diagnosis. - Gözde Merve Demirci; Jiachen Yao; Ming-Chih Ho; Xiaoling Hu 002; Wei-Chi Wu; Chao Chen 012; Chia-Ling Tsai (CoRR, 2024)

Backdooring Vision-Language Models with Out-Of-Distribution Data. - Weimin Lyu; Jiachen Yao; Saumya Gupta; Lu Pang 006; Tao Sun 009; Lingjie Yi; Lijie Hu; Haibin Ling; Chao Chen 012 (ICLR, 2025)

Geometry of Long-Tailed Representation Learning: Rebalancing Features for Skewed Distributions. - Lingjie Yi; Jiachen Yao; Weimin Lyu; Haibin Ling; Raphael Douady; Chao Chen 012 (ICLR, 2025)

Recovering manifold representations via unsupervised meta-learning. - Yunye Gong; Jiachen Yao; Ruyi Lian; Xiao Lin; Chao Chen; Ajay Divakaran; Yi Yao (Frontiers Comput. Sci., 2025)

A Theoretical Study of Neural Network Expressive Power via Manifold Topology. - Jiachen Yao; Lingjie Yi; Mayank Goswami 001; Chao Chen 012 (Trans. Mach. Learn. Res., 2025)

A lightweight diagnosis method for gear fault based on multi-path convolutional neural networks with attention mechanism. - Tianming Chen; Manyi Wang; Yilin Jiang; Jiachen Yao; Ming Li (Appl. Intell., 2025)

Guided Diffusion Sampling on Function Spaces with Applications to PDEs. - Jiachen Yao; Abbas Mammadov; Julius Berner; Gavin Kerrigan; Jong Chul Ye; Kamyar Azizzadenesheli; Anima Anandkumar (CoRR, 2025)

EquiReg: Equivariance Regularized Diffusion for Inverse Problems. - Bahareh Tolooshams; Aditi Chandrashekar; Rayhan Zirvi; Abbas Mammadov; Jiachen Yao; Chuwei Wang; Anima Anandkumar (CoRR, 2025)