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ORCIDYilun Xu
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 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) - [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 - [i27]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) - [i26]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) - [i25]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) - [i24]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) - [i23]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) - [i22]Chaobing Zheng, Yilun Xu, Weihai Chen, Shiqian Wu, Zhengguo Li:
Neural Augmentation Based Panoramic High Dynamic Range Stitching. CoRR abs/2409.04679 (2024) - [i21]Sulin Liu, Juno Nam, Andrew Campbell, Hannes Stärk, Yilun Xu, Tommi S. Jaakkola, Rafael Gómez-Bombarelli:
Think While You Generate: Discrete Diffusion with Planned Denoising. CoRR abs/2410.06264 (2024) - [i20]Kushagra Pandey, Jaideep Pathak, Yilun Xu, Stephan Mandt, Michael S. Pritchard, Arash Vahdat, Morteza Mardani:
Heavy-Tailed Diffusion Models. CoRR abs/2410.14171 (2024) - [i19]Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie:
Truncated Consistency Models. CoRR abs/2410.14895 (2024) - [i18]Peter Holderrieth, Yilun Xu, Tommi S. Jaakkola:
Hamiltonian Score Matching and Generative Flows. CoRR abs/2410.20470 (2024) - [i17]Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat:
Energy-Based Diffusion Language Models for Text Generation. CoRR abs/2410.21357 (2024) - 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 - [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
- [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) - [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 - [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
- [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 - [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
- [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 - [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)
2010 – 2019
- 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 - [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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last updated on 2024-12-02 21:28 CET by the dblp team
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