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Xiyang Luo
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2020 – today
- 2023
- [j3]Weicheng Kuo, A. J. Piergiovanni, Dahun Kim, Xiyang Luo, Benjamin Caine, Wei Li, Abhijit S. Ogale, Luowei Zhou, Andrew M. Dai, Zhifeng Chen, Claire Cui, Anelia Angelova:
MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks. Trans. Mach. Learn. Res. 2023 (2023) - [c9]Xiyang Luo, Michael Goebel, Elnaz Barshan, Feng Yang:
LECA: A learned approach for efficient cover-agnostic watermarking. Media Watermarking, Security, and Forensics 2023: 1-6 - [i16]Weicheng Kuo, A. J. Piergiovanni, Dahun Kim, Xiyang Luo, Benjamin Caine, Wei Li, Abhijit S. Ogale, Luowei Zhou, Andrew M. Dai, Zhifeng Chen, Claire Cui, Anelia Angelova:
MaMMUT: A Simple Architecture for Joint Learning for MultiModal Tasks. CoRR abs/2303.16839 (2023) - 2022
- [c8]Innfarn Yoo, Huiwen Chang, Xiyang Luo, Ondrej Stava, Ce Liu, Peyman Milanfar, Feng Yang:
Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings. CVPR 2022: 10021-10030 - [i15]Xiyang Luo, Michael Goebel, Elnaz Barshan, Feng Yang:
LECA: A Learned Approach for Efficient Cover-agnostic Watermarking. CoRR abs/2206.10813 (2022) - 2021
- [j2]Hossein Talebi Esfandarani
, Damien Kelly, Xiyang Luo
Better Compression With Deep Pre-Editing. IEEE Trans. Image Process. 30: 6673-6685 (2021) - [c7]Xiyang Luo, Hossein Talebi, Feng Yang, Michael Elad, Peyman Milanfar:
The Rate-Distortion-Accuracy Tradeoff: JPEG Case Study. DCC 2021: 354 - [i14]Xiyang Luo, Yinxiao Li, Huiwen Chang, Ce Liu, Peyman Milanfar, Feng Yang:
DVMark: A Deep Multiscale Framework for Video Watermarking. CoRR abs/2104.12734 (2021) - [i13]Innfarn Yoo, Huiwen Chang, Xiyang Luo, Ondrej Stava, Ce Liu, Peyman Milanfar, Feng Yang:
Deep 3D-to-2D Watermarking: Embedding Messages in 3D Meshes and Extracting Them from 2D Renderings. CoRR abs/2104.13450 (2021) - [i12]Pascal Tom Getreuer, Peyman Milanfar, Xiyang Luo:
Solving Image PDEs with a Shallow Network. CoRR abs/2110.08327 (2021) - 2020
- [c6]Xiyang Luo, Ruohan Zhan, Huiwen Chang, Feng Yang, Peyman Milanfar:
Distortion Agnostic Deep Watermarking. CVPR 2020: 13545-13554 - [c5]Innfarn Yoo, Xiyang Luo, Yilin Wang, Feng Yang, Peyman Milanfar:
GIFnets: Differentiable GIF Encoding Framework. CVPR 2020: 14461-14470 - [i11]Xiyang Luo, Ruohan Zhan, Huiwen Chang, Feng Yang, Peyman Milanfar:
Distortion Agnostic Deep Watermarking. CoRR abs/2001.04580 (2020) - [i10]Hossein Talebi, Damien Kelly, Xiyang Luo, Ignacio Garcia-Dorado, Feng Yang, Peyman Milanfar, Michael Elad:
Better Compression with Deep Pre-Editing. CoRR abs/2002.00113 (2020) - [i9]Innfarn Yoo, Xiyang Luo, Yilin Wang, Feng Yang, Peyman Milanfar:
GIFnets: Differentiable GIF Encoding Framework. CoRR abs/2006.13434 (2020) - [i8]Xiyang Luo, Hossein Talebi, Feng Yang, Michael Elad, Peyman Milanfar:
The Rate-Distortion-Accuracy Tradeoff: JPEG Case Study. CoRR abs/2008.00605 (2020)
2010 – 2019
- 2019
- [c4]Yiling Qiao, Chang Shi, Chenjian Wang, Hao Li, Matt Haberland, Xiyang Luo, Andrew M. Stuart
Uncertainty quantification for semi-supervised multi-class classification in image processing and ego-motion analysis of body-worn videos. Image Processing: Algorithms and Systems 2019 - [c3]Zhijian Li, Xiyang Luo, Bao Wang, Andrea L. Bertozzi
A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting. WCGO 2019: 730-739 - [i7]Zhijian Li, Xiyang Luo, Bao Wang, Andrea L. Bertozzi, Jack Xin:
A Study on Graph-Structured Recurrent Neural Networks and Sparsification with Application to Epidemic Forecasting. CoRR abs/1902.05113 (2019) - 2018
- [b1]Xiyang Luo:
Analysis and Application of Graph-Based Semi-Supervised Learning Methods. University of California, Los Angeles, USA, 2018 - [j1]Andrea L. Bertozzi
Uncertainty Quantification in Graph-Based Classification of High Dimensional Data. SIAM/ASA J. Uncertain. Quantification 6(2): 568-595 (2018) - [c2]Bao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley J. Osher:
Deep Neural Nets with Interpolating Function as Output Activation. NeurIPS 2018: 751-761 - [i6]Bao Wang, Xiyang Luo, Zhen Li, Wei Zhu, Zuoqiang Shi, Stanley J. Osher:
Deep Learning with Data Dependent Implicit Activation Function. CoRR abs/1802.00168 (2018) - [i5]Alan Mackey, Xiyang Luo, Elad Eban:
Constrained Classification and Ranking via Quantiles. CoRR abs/1803.00067 (2018) - [i4]Bao Wang, Xiyang Luo, Fangbo Zhang, Baichuan Yuan, Andrea L. Bertozzi, P. Jeffrey Brantingham:
Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data. CoRR abs/1804.00684 (2018) - [i3]Stanley J. Osher, Bao Wang, Penghang Yin, Xiyang Luo, Minh Pham
Laplacian Smoothing Gradient Descent. CoRR abs/1806.06317 (2018) - [i2]Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Huai-hsin Chi, Elad Eban, Xiyang Luo, Alan Mackey, Ofer Meshi:
Seq2Slate: Re-ranking and Slate Optimization with RNNs. CoRR abs/1810.02019 (2018) - 2017
- [i1]Andrea L. Bertozzi, Xiyang Luo, Andrew M. Stuart, Konstantinos C. Zygalakis:
Uncertainty Quantification in the Classification of High Dimensional Data. CoRR abs/1703.08816 (2017) - 2016
- [c1]Xiyang Luo, Brendt Wohlberg
Convolutional Laplacian sparse coding. SSIAI 2016: 133-136
Coauthor Index
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