Yilun Xu

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 41

Top Topics

Diffusion Models

Top Venues

Publications

Neelay Fruitwala, Gang Huang, Yilun Xu, Abhi D. Rajagopala, Akel Hashim, Ravi Naik, Kasra Nowrouzi, David Santiago, Irfan Siddiqi
Distributed Architecture for FPGA-based Superconducting Qubit Control. CoRR (2024)
Zhuonan Zheng, Sheng Zhou, Hongjia Xu, Ming Gu, Yilun Xu, Ao Li, Yuhong Li, Jingjun Gu, Jiajun Bu
Heterophilous Distribution Propagation for Graph Neural Networks. CoRR (2024)
Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. CoRR (2024)
Hanqun Cao, Cheng Tan, Zhangyang Gao, Yilun Xu, Guangyong Chen, Pheng-Ann Heng, Stan Z. Li
A Survey on Generative Diffusion Models. IEEE Trans. Knowl. Data Eng. 36 (7) (2024)
Cheng Chu, Zhenxiao Fu, Yilun Xu, Gang Huang, Hausi A. Müller, Fan Chen, Lei Jiang
TITAN: A Distributed Large-Scale Trapped-Ion NISQ Computer. CoRR (2024)
Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. ICLR (2024)
Zhenxiao Fu, Min Yang, Cheng Chu, Yilun Xu, Gang Huang, Fan Chen
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines. CoRR (2024)
Xiaoli Wu, Hao Wu, Shouliang Miao, Guoquan Cao, Huang Su, Jie Pan, Yilun Xu
Deep learning prediction of esophageal squamous cell carcinoma invasion depth from arterial phase enhanced CT images: a binary classification approach. BMC Medical Informatics Decis. Mak. 24 (1) (2024)
Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. ICLR (2023)
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. CoRR (2023)
Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. CoRR (2023)
Gang Huang, Yilun Xu, Neelay Fruitwala, Abhi D. Rajagopala, Kasra Nowrouzi, Ravi Naik, David Santiago, Irfan Siddiqi
QubiC 2.0: A Flexible Advanced Full Stack Quantum Bit Control System. QCE (2023)
Ziming Liu, Di Luo, Yilun Xu, Tommi S. Jaakkola, Max Tegmark
GenPhys: From Physical Processes to Generative Models. CoRR (2023)
Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola
Restart Sampling for Improving Generative Processes. NeurIPS (2023)
Chaobing Zheng, Yilun Xu, Weihai Chen, Shiqian Wu, Zhengguo Li
Physics-Driven Deep Panoramic Imaging for High Dynamic Range Scenes. IECON (2023)
Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola
Restart Sampling for Improving Generative Processes. CoRR (2023)
Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. CoRR (2023)
Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. ICML (2023)
Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
Poisson Flow Generative Models. NeurIPS (2022)
Yilun Xu, Hao He, Tianxiao Shen, Tommi S. Jaakkola
Controlling Directions Orthogonal to a Classifier. ICLR (2022)
Neelay Fruitwala, Yilun Xu, Ravi Naik, Kasra Nowrouzi, Gang Huang
Distributed Processor for FPGA-based Superconducting Qubit Control. QCE (2022)
Yilun Xu, Hao He, Tianxiao Shen, Tommi Jaakkola
Controlling Directions Orthogonal to a Classifier. CoRR (2022)
Yilun Xu, Ziyang Liu, Xingming Wu, Weihai Chen, Changyun Wen, Zhengguo Li
Deep Joint Demosaicing and High Dynamic Range Imaging Within a Single Shot. IEEE Trans. Circuits Syst. Video Technol. 32 (7) (2022)
Mohsen Bahrami, Yilun Xu, Miles Tweed, Burçin Bozkaya, Alex 'Sandy' Pentland
Using gravity model to make store closing decisions: A data driven approach. Expert Syst. Appl. 205 (2022)
Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola
Poisson Flow Generative Models. CoRR (2022)
Yilun Xu, Ziyang Liu, Xingming Wu, Weihai Chen, Zhengguo Li
Restoration of HDR Images for SVE-Based HDRI via a Novel DCNN. ICME (2021)
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? ICML (2021)
Yilun Xu, Tommi Jaakkola
Learning Representations that Support Robust Transfer of Predictors. CoRR (2021)
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
Anytime Sampling for Autoregressive Models via Ordered Autoencoding. CoRR (2021)
Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon
Anytime Sampling for Autoregressive Models via Ordered Autoencoding. ICLR (2021)
Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? CoRR (2021)
Yilun Xu, Zhengguo Li, Weihai Chen, Changyun Wen
Color Mapping Functions For HDR Panorama Imaging: Weighted Histogram Averaging. CoRR (2021)
Yilun Xu, Ziyang Liu, Xingming Wu, Weihai Chen, Changyun Wen, Zhengguo Li
Deep Joint Demosaicing and High Dynamic Range Imaging within a Single Shot. CoRR (2021)
Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon
A Theory of Usable Information Under Computational Constraints. CoRR (2020)
Xinwei Sun, Yilun Xu, Peng Cao, Yuqing Kong, Lingjing Hu, Shanghang Zhang, Yizhou Wang
TCGM: An Information-Theoretic Framework for Semi-Supervised Multi-Modality Learning. CoRR (2020)
Xinwei Sun, Yilun Xu, Peng Cao, Yuqing Kong, Lingjing Hu, Shanghang Zhang, Yizhou Wang
TCGM: An Information-Theoretic Framework for Semi-supervised Multi-modality Learning. ECCV (3) (2020)
Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon
A Theory of Usable Information under Computational Constraints. ICLR (2020)
Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds. CoRR (2019)
Yilun Xu, Peng Cao, Yuqing Kong, Yizhou Wang
L_DMI: An Information-theoretic Noise-robust Loss Function. CoRR (2019)
Yilun Xu, Peng Cao, Yuqing Kong, Yizhou Wang
L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise. NeurIPS (2019)
Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds. ICLR (Poster) (2019)