Convolutional Laplacian sparse coding. - Xiyang Luo; Brendt Wohlberg (SSIAI, 2016)

Uncertainty Quantification in the Classification of High Dimensional Data. - Andrea L. Bertozzi; Xiyang Luo; Andrew M. Stuart; Konstantinos C. Zygalakis (CoRR, 2017)

Deep Neural Nets with Interpolating Function as Output Activation. - Bao Wang 001; Xiyang Luo; Zhen Li 029; Wei Zhu 007; Zuoqiang Shi; Stanley J. Osher (NeurIPS, 2018)

Deep Learning with Data Dependent Implicit Activation Function. - Bao Wang 001; Xiyang Luo; Zhen Li 029; Wei Zhu 007; Zuoqiang Shi; Stanley J. Osher (CoRR, 2018)

Constrained Classification and Ranking via Quantiles. - Alan Mackey; Xiyang Luo; Elad Eban (CoRR, 2018)

Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data. - Bao Wang 001; Xiyang Luo; Fangbo Zhang; Baichuan Yuan; Andrea L. Bertozzi; P. Jeffrey Brantingham (CoRR, 2018)

Laplacian Smoothing Gradient Descent. - Stanley J. Osher; Bao Wang 001; Penghang Yin; Xiyang Luo; Minh Pham 003; Alex Tong Lin (CoRR, 2018)

Seq2Slate: Re-ranking and Slate Optimization with RNNs. - Irwan Bello; Sayali Kulkarni; Sagar Jain; Craig Boutilier; Ed Huai-hsin Chi; Elad Eban; Xiyang Luo; Alan Mackey; Ofer Meshi (CoRR, 2018)

Uncertainty Quantification in Graph-Based Classification of High Dimensional Data. - Andrea L. Bertozzi; Xiyang Luo; Andrew M. Stuart; Konstantinos C. Zygalakis (SIAM/ASA J. Uncertain. Quantification, 2018)

Analysis and Application of Graph-Based Semi-Supervised Learning Methods. - Xiyang Luo (2018)

Uncertainty quantification for semi-supervised multi-class classification in image processing and ego-motion analysis of body-worn videos. - Yiling Qiao; Chang Shi; Chenjian Wang; Hao Li; Matt Haberland; Xiyang Luo; Andrew M. Stuart; Andrea L. Bertozzi (Image Processing: Algorithms and Systems, 2019)

A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting. - Zhijian Li; Xiyang Luo; Bao Wang 001; Andrea L. Bertozzi; Jack Xin (WCGO, 2019)

Distortion Agnostic Deep Watermarking. - Xiyang Luo; Ruohan Zhan; Huiwen Chang; Feng Yang 008; Peyman Milanfar (CVPR, 2020)

GIFnets: Differentiable GIF Encoding Framework. - Innfarn Yoo; Xiyang Luo; Yilin Wang 001; Feng Yang 008; Peyman Milanfar (CVPR, 2020)

Better Compression with Deep Pre-Editing. - Hossein Talebi; Damien Kelly; Xiyang Luo; Ignacio Garcia-Dorado; Feng Yang 008; Peyman Milanfar; Michael Elad (CoRR, 2020)

The Rate-Distortion-Accuracy Tradeoff: JPEG Case Study. - Xiyang Luo; Hossein Talebi; Feng Yang 008; Michael Elad; Peyman Milanfar (DCC, 2021)

Solving Image PDEs with a Shallow Network. - Pascal Tom Getreuer; Peyman Milanfar; Xiyang Luo (CoRR, 2021)

Better Compression With Deep Pre-Editing. - Hossein Talebi Esfandarani; Damien Kelly; Xiyang Luo; Ignacio Garcia-Dorado; Feng Yang 008; Peyman Milanfar; Michael Elad (IEEE Trans. Image Process., 2021)

Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings. - Innfarn Yoo; Huiwen Chang; Xiyang Luo; Ondrej Stava; Ce Liu 001; Peyman Milanfar; Feng Yang 008 (CVPR, 2022)

LECA: A learned approach for efficient cover-agnostic watermarking. - Xiyang Luo; Michael Goebel; Elnaz Barshan; Feng Yang (Media Watermarking, Security, and Forensics, 2023)

MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks. - Weicheng Kuo; A. J. Piergiovanni; Dahun Kim; Xiyang Luo; Benjamin Caine; Wei Li 133; Abhijit S. Ogale; Luowei Zhou; Andrew M. Dai; Zhifeng Chen; Claire Cui; Anelia Angelova (Trans. Mach. Learn. Res., 2023)

DVMark: A Deep Multiscale Framework for Video Watermarking. - Xiyang Luo; Yinxiao Li; Huiwen Chang; Ce Liu 001; Peyman Milanfar; Feng Yang 008 (IEEE Trans. Image Process., 2025)