1. Nian Xue - Google Scholar
New York University - Cited by 768 - Security - IoT - Machine Learning - Deep Learning - Blockchain
New York University - Cited by 771 - Security - IoT - Machine Learning - Deep Learning - Blockchain
2. Nian Xue | IEEE Xplore Author Details
Nian Xue received the B.E. degree from Xi'an Jiaotong University in 2004. He is currently pursuing the master's degree with Xi'an Jiaotong-Liverpool University.
Your support ID is: 8203162003781848852.
3. Nian Xue | Papers With Code
Based on the collected data, we evaluate the prediction capabilities of ChatGPT and a two-stage classification approach based on the Doc2Vec model with various ...
Papers by Nian Xue with links to code and results.
4. Nian Xue - Google Scholar
Maximum Gaussian mixture model for classification. J Zhang, X Hong, SU Guan, X Zhao, H Xin, N Xue. 2016 8th International Conference on Information Technology ...
New York University - 引用: 771 件 - Security - IoT - Machine Learning - Deep Learning - Blockchain
5. Evaluation of Machine Learning Models for Aqueous Solubility ...
Jun 11, 2024 · This paper explores and evaluates the predictability of multiple machine learning models in the aqueous solubility of compounds.
Determining the aqueous solubility of the chemical compound is of great importance in-silico drug discovery. However, correctly and rapidly predicting the aqueous solubility remains a challenging task. This paper explores and evaluates the predictability of multiple machine learning models in the aqueous solubility of compounds. Specifically, we apply a series of machine learning algorithms, including Random Forest, XG-Boost, LightGBM, and CatBoost, on a well-established aqueous solubility dataset (i. e., the Huuskonen dataset) of over 1200 compounds. Experimental results show that even traditional machine learning algorithms can achieve satisfactory performance with high accuracy. In addition, our investigation goes beyond mere prediction accuracy, delving into the interpretability of models to identify key features and understand the molecular properties that influence the predicted outcomes. This study sheds light on the ability to use machine learning approaches to predict compound solubility, significantly shortening the time that researchers spend on new drug discovery. ### Competing Interest Statement The authors have declared no competing interest.
6. Nian Xue wallpapers - wallhaven.cc
Nian Xue · Nian Nian · Ting Xue · XQ Xue · Nian · Xue YuSheng · Xue Lu · Li xue · Nian (Arknights) ...
Nian Xue wallpapers
7. Nianwen Xue - Google Scholar
Missing: Nian | Show results with:Nian
Professor, Computer Science Department, Brandeis University - Cited by 11,190 - computational linguistics - natural language processing - Chinese language processing
8. Nian Xue - Google Scholar
Nian Xue. New York University. ยืนยันอีเมลแล้วที่ nyu.edu. SecurityIoT ... Maximum Gaussian mixture model for classification. J Zhang, X Hong, SU Guan ...
New York University - อ้างอิงโดย 771 รายการ - Security - IoT - Machine Learning - Deep Learning - Blockchain
9. Jianwen Xie's Homepage - UCLA Statistics & Data Science
Hierarchical Sparse FRAME Model (CVPR 2017 by Xie et al.) Deep FRAME ... --Ruiqi Gao, Jianwen Xie, Xue-Xin Wei, Song-Chun Zhu, Ying Nian Wu; --Thirty ...
10. MOBIMEDIA 2016 - Accepted Papers
Nian Xue (Department of Computer Science and Software Engineering, Xi'an ... A Recommender System Model based on Commodity-Purchase-Cycle Classification.
Zhang Yan-li (Guangdong AIB Polytechnic College), JIANG Guo-liang (Xidian University), Song Bin (Xidian University)
11. lao nian chi dai huan zhe shui mian zhang ai de lin chuang te zheng li ...
Establishment and pathological observation of rabbit model with fungal keratitis ... lao nian gao xue ya nao chu xue 98 li ji zhen wei chuang shou shu zhi liao ...
Chinese Journal of Gerontology lao nian chi dai huan zhe shui mian zhang ai de lin chuang te zheng 2012 Issue 1005-9202
12. STRAIN HARDENING EXPONENT MODEL AND ITS INFLUENCE ON ...
... Nian-nian, XUE Bing-han, LI Bin. STRAIN HARDENING EXPONENT MODEL AND ITS INFLUENCE ON FAILURE PRESSURE OF STEEL PIPELINE[J]. Engineering Mechanics. DOI ...
Based on the strain hardening effect of steel materials and deformation instability theory, the numerical solution of strain hardening exponent is obtained and its influence on the ultimate internal pressure bearing capacity of pipes is clarified.According to the actual burst pressure data of intact pipeline, the applicable range of strain hardening index is developed.The results show that: the strain hardening exponent can be obtained by solving the yield ratio and yield strain, and the numerical solution is slightly smaller than the true value. The hardening performance of pipelines enhances with the increase of strain hardening exponent
n and hardening coefficientK . The higher the strength grade of steel, the smaller the hardening exponentn and the lower the failure stress. The failure strain of the pipeline is equal to half of the true strain corresponding to the tensile strength. Whether or not to consider the strain hardening of steel materials, the difference between failure pressure errors is 2.24%~6.08%, in which von Mises yield is more sensitive to the computational model of strain hardening index.
13. [2405.16852] EM Distillation for One-step Diffusion Models - arXiv
May 27, 2024 · EM Distillation for One-step Diffusion Models. Authors:Sirui Xie, Zhisheng Xiao, Diederik P Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick ...
While diffusion models can learn complex distributions, sampling requires a computationally expensive iterative process. Existing distillation methods enable efficient sampling, but have notable limitations, such as performance degradation with very few sampling steps, reliance on training data access, or mode-seeking optimization that may fail to capture the full distribution. We propose EM Distillation (EMD), a maximum likelihood-based approach that distills a diffusion model to a one-step generator model with minimal loss of perceptual quality. Our approach is derived through the lens of Expectation-Maximization (EM), where the generator parameters are updated using samples from the joint distribution of the diffusion teacher prior and inferred generator latents. We develop a reparametrized sampling scheme and a noise cancellation technique that together stabilizes the distillation process. We further reveal an interesting connection of our method with existing methods that minimize mode-seeking KL. EMD outperforms existing one-step generative methods in terms of FID scores on ImageNet-64 and ImageNet-128, and compares favorably with prior work on distilling text-to-image diffusion models.
14. [PDF] The Theory of Dispersion Models - Semantic Scholar
Introduction to dispersion models natural exponential families exponential dispersion models tweedie models proper dispersion models ... Nian-Sheng TangB. WeiXue- ...
15. Jianwen Xie - DBLP
Jianwen Xie: Generative Modeling and Unsupervised Learning in Computer Vision. University of California, Los Angeles ...
List of computer science publications by Jianwen Xie
16. [PDF] RUIQI GAO's CV for Application
Jianwen Xie*, Zilong Zheng*, Ruiqi Gao, Wenguan Wang, SongChun Zhu and Ying Nian Wu. “Generative VoxelNet: Learning EnergyBased Models for 3D Shape Synthesis ...
17. Dehong Xu - OpenReview
An Investigation of Conformal Isometry Hypothesis for Grid Cells · Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu. Published: 31 Dec 2023, Last ...
Dehong Xu (Preferred)
18. shuxuemoxing : mathematical mo... : shù xué mó xíng | Definition
数学模型 Trad. 數學模型. shù xué mó xíng. mathematical model. Browse Dictionary. 数字版权管理 | ShuziBanquanGuanli | Shu zi Ban quan Guan li ...
shuxuemoxing definition at Chinese.Yabla.com, a free online dictionary with English, Mandarin Chinese, Pinyin, Strokes & Audio. Look it up now!
19. 成果及论文 - 薛小松课题组 - X-MOL
Tao-Bin He#, Bing-Chao Yan#, Yuan-Fei Zhou#, Yue-Qian Sang#, Xiao-Nian Li, Han-Dong Sun, Chu Wang, Xiao-Song Xue* and Pema-Tenzin Puno*, Chem. Sci. 2024, 15, ...
X-MOL学术平台，Top期刊论文图文内容每日更新，海内外课题组信息，行业新闻文摘，化学类网址导航，化学软件和数据库导航，及更多其他内容
20. Publications - NYU Abu Dhabi
... Model for Classification", 8th International Conference on Information Technology in Medicine and Education (ITME) pp587-591, (2016). Xue, Nian, Lulu Liang ...
Xue, Nian, Chenglong Jiang, Xin Huang, and Dawei Liu. "A Role-Based Access Control System for Intelligent Buildings." In International Conference on Network and System Security, pp. 710-720. Springer, Cham, 2017.
21. Learning Inhomogeneous FRAME Models for Object Patterns
Learning Inhomogeneous FRAME Models for Object Patterns. Jianwen Xie, Wenze Hu, Song-Chun Zhu, Ying Nian Wu; Proceedings of the IEEE Conference on Computer ...
Learning Inhomogeneous FRAME Models for Object Patterns
