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Journal Articles
- 2024
[j4]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): 3 (2024)- [j3]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): 2814-2830 (2024) - 2022
- [j2]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: 117703 (2022) - [j1]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): 4255-4270 (2022)
Conference and Workshop Papers
- 2024
- [c19]Cheng Chu, Zhenxiao Fu, Yilun Xu, Gang Huang, Hausi A. Müller, Fan Chen, Lei Jiang:
TITAN: A Fast and Distributed Large-Scale Trapped-Ion NISQ Computer. DAC 2024: 54:1-54:6 - [c18]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 - [c17]Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis:
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. ICML 2024 - [c16]Zhenxiao Fu, Min Yang, Cheng Chu, Yilun Xu, Gang Huang, Fan Chen:
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines. IJCNN 2024: 1-8 - 2023
- [c15]Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola:
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. ICLR 2023 - [c14]Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola:
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. ICML 2023: 38566-38591 - [c13]Chaobing Zheng, Yilun Xu, Weihai Chen, Shiqian Wu, Zhengguo Li:
Physics-Driven Deep Panoramic Imaging for High Dynamic Range Scenes. IECON 2023: 1-6 - [c12]Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola:
Restart Sampling for Improving Generative Processes. NeurIPS 2023 - [c11]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: 248-249 - 2022
- [c10]Yilun Xu, Hao He, Tianxiao Shen, Tommi S. Jaakkola:
Controlling Directions Orthogonal to a Classifier. ICLR 2022 - [c9]Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola:
Poisson Flow Generative Models. NeurIPS 2022 - [c8]Neelay Fruitwala, Yilun Xu, Ravi Naik, Kasra Nowrouzi, Gang Huang:
Distributed Processor for FPGA-based Superconducting Qubit Control. QCE 2022: 763-764 - 2021
- [c7]Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon:
Anytime Sampling for Autoregressive Models via Ordered Autoencoding. ICLR 2021 - [c6]Yilun Xu, Ziyang Liu, Xingming Wu, Weihai Chen, Zhengguo Li:
Restoration of HDR Images for SVE-Based HDRI via a Novel DCNN. ICME 2021: 1-6 - [c5]Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville:
Can Subnetwork Structure Be the Key to Out-of-Distribution Generalization? ICML 2021: 12356-12367 - 2020
- [c4]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: 171-188 - [c3]Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon:
A Theory of Usable Information under Computational Constraints. ICLR 2020 - 2019
- [c2]Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang:
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds. ICLR (Poster) 2019 - [c1]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: 6222-6233
Informal and Other Publications
- 2024
- [i22]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 abs/2402.11021 (2024) - [i21]Zhenxiao Fu, Min Yang, Cheng Chu, Yilun Xu, Gang Huang, Fan Chen:
QuantumLeak: Stealing Quantum Neural Networks from Cloud-based NISQ Machines. CoRR abs/2403.10790 (2024) - [i20]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 abs/2404.15260 (2024) - [i19]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 abs/2405.20640 (2024) - [i18]Yilun Xu, Gabriele Corso, Tommi S. Jaakkola, Arash Vahdat, Karsten Kreis:
DisCo-Diff: Enhancing Continuous Diffusion Models with Discrete Latents. CoRR abs/2407.03300 (2024) - [i17]Chaobing Zheng, Yilun Xu, Weihai Chen, Shiqian Wu, Zhengguo Li:
Neural Augmentation Based Panoramic High Dynamic Range Stitching. CoRR abs/2409.04679 (2024) - 2023
- [i16]Yilun Xu, Shangyuan Tong, Tommi S. Jaakkola:
Stable Target Field for Reduced Variance Score Estimation in Diffusion Models. CoRR abs/2302.00670 (2023) - [i15]Yilun Xu, Ziming Liu, Yonglong Tian, Shangyuan Tong, Max Tegmark, Tommi S. Jaakkola:
PFGM++: Unlocking the Potential of Physics-Inspired Generative Models. CoRR abs/2302.04265 (2023) - [i14]Ziming Liu, Di Luo, Yilun Xu, Tommi S. Jaakkola, Max Tegmark:
GenPhys: From Physical Processes to Generative Models. CoRR abs/2304.02637 (2023) - [i13]Yilun Xu, Mingyang Deng, Xiang Cheng, Yonglong Tian, Ziming Liu, Tommi S. Jaakkola:
Restart Sampling for Improving Generative Processes. CoRR abs/2306.14878 (2023) - [i12]Gabriele Corso, Yilun Xu, Valentin De Bortoli, Regina Barzilay, Tommi S. Jaakkola:
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models. CoRR abs/2310.13102 (2023) - 2022
- [i11]Yilun Xu, Hao He, Tianxiao Shen, Tommi S. Jaakkola:
Controlling Directions Orthogonal to a Classifier. CoRR abs/2201.11259 (2022) - [i10]Yilun Xu, Ziming Liu, Max Tegmark, Tommi S. Jaakkola:
Poisson Flow Generative Models. CoRR abs/2209.11178 (2022) - 2021
- [i9]Yilun Xu, Yang Song, Sahaj Garg, Linyuan Gong, Rui Shu, Aditya Grover, Stefano Ermon:
Anytime Sampling for Autoregressive Models via Ordered Autoencoding. CoRR abs/2102.11495 (2021) - [i8]Dinghuai Zhang, Kartik Ahuja, Yilun Xu, Yisen Wang, Aaron C. Courville:
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? CoRR abs/2106.02890 (2021) - [i7]Yilun Xu, Tommi S. Jaakkola:
Learning Representations that Support Robust Transfer of Predictors. CoRR abs/2110.09940 (2021) - [i6]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 abs/2111.07281 (2021) - [i5]Yilun Xu, Zhengguo Li, Weihai Chen, Changyun Wen:
Color Mapping Functions For HDR Panorama Imaging: Weighted Histogram Averaging. CoRR abs/2111.07283 (2021) - 2020
- [i4]Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon:
A Theory of Usable Information Under Computational Constraints. CoRR abs/2002.10689 (2020) - [i3]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 abs/2007.06793 (2020) - 2019
- [i2]Peng Cao, Yilun Xu, Yuqing Kong, Yizhou Wang:
Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds. CoRR abs/1905.13436 (2019) - [i1]Yilun Xu, Peng Cao, Yuqing Kong, Yizhou Wang:
L_DMI: An Information-theoretic Noise-robust Loss Function. CoRR abs/1909.03388 (2019)
Coauthor Index
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