• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 1,057 matches

• 2021
• 
  Rezzy Eko Caraka, Youngjo Lee, Rung Ching Chen, Toni Toharudin, Prana Ugiana Gio, Robert Kurniawan, Bens Pardamean:
  Cluster Around Latent Variable for Vulnerability Towards Natural Hazards, Non-Natural Hazards, Social Hazards in West Papua. IEEE Access 9: 1972-1986 (2021)
• 
  Hao Xiong, Yuan Yan Tang, Fionn Murtagh, Leszek Rutkowski, Shlomo Berkovsky:
  A diversified shared latent variable model for efficient image characteristics extraction and modelling. Neurocomputing 421: 244-259 (2021)
• 
  Eunji Kim, Dongseon Lee, Youngchun Kwon, Min Sik Park, Youn-Suk Choi:
  Valid, Plausible, and Diverse Retrosynthesis Using Tied Two-Way Transformers with Latent Variables. J. Chem. Inf. Model. 61(1): 123-133 (2021)
• 
  Guoli Song, Shuhui Wang, Qingming Huang, Qi Tian:
  Harmonized Multimodal Learning with Gaussian Process Latent Variable Models. IEEE Trans. Pattern Anal. Mach. Intell. 43(3): 858-872 (2021)
• 
  Jinxing Li, Guangming Lu, Bob Zhang, Jane You, David Zhang:
  Shared Linear Encoder-Based Multikernel Gaussian Process Latent Variable Model for Visual Classification. IEEE Trans. Cybern. 51(2): 534-547 (2021)
• 
  Boris Hayete, Fred Gruber, Anna Decker, Raymond Yan:
  Identification of Latent Variables From Graphical Model Residuals. CoRR abs/2101.02332 (2021)
• 
  Zixu Wang, Yishu Miao, Lucia Specia:
  Latent Variable Models for Visual Question Answering. CoRR abs/2101.06399 (2021)
• 
  Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt:
  Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. CoRR abs/2101.07046 (2021)
• 
  Danushka Bollegala, Huda Hakami, Yuichi Yoshida, Ken-ichi Kawarabayashi:
  RelWalk A Latent Variable Model Approach to Knowledge Graph Embedding. CoRR abs/2101.10070 (2021)
• 
  Rui Chen, Sanjeeb Dash, Tian Gao:
  Integer Programming for Causal Structure Learning in the Presence of Latent Variables. CoRR abs/2102.03129 (2021)
• 
  Nicholas Oune, Ramin Bostanabad:
  Latent Map Gaussian Processes for Mixed Variable Metamodeling. CoRR abs/2102.03935 (2021)
• 
  Sara Mohammad Taheri, Robert Osazuwa Ness, Jeremy Zucker, Olga Vitek:
  Do-calculus enables causal reasoning with latent variable models. CoRR abs/2102.06626 (2021)
• 
  Severi Rissanen, Pekka Marttinen:
  A Critical Look At The Identifiability of Causal Effects with Deep Latent Variable Models. CoRR abs/2102.06648 (2021)
• 2020
• 
  Dinghan Shen:
  Deep Latent-Variable Models for Natural Language Understanding and Generation. Duke University, Durham, NC, USA, 2020
• 
  Fabricio Alves de Almeida, Simone Carneiro Streitenberger, Alexandre F. Torres, Anderson Paulo de Paiva, José Henrique de Freitas Gomes:
  A Gage Study Through the Weighting of Latent Variables Under Orthogonal Rotation. IEEE Access 8: 183557-183570 (2020)
• 
  Yun Jing, Wanglin Xu, Siye Guo, Yingjin Zhang:
  Analysis of Choice Behaviors of Railway Shippers for Freight Services Based on a Fuzzy Integrated Choice and Latent Variable Model. IEEE Access 8: 64399-64410 (2020)
• 
  Shaowen Lu, Shuyu Huang:
  Segmentation of Multivariate Industrial Time Series Data Based on Dynamic Latent Variable Predictability. IEEE Access 8: 112092-112103 (2020)
• 
  Aghila Rajagopal, A. Ramachandran, K. Shankar, Manju Khari, Sudan Jha, Yongju Lee, Gyanendra Prasad Joshi:
  Fine-Tuned Residual Network-Based Features With Latent Variable Support Vector Machine-Based Optimal Scene Classification Model for Unmanned Aerial Vehicles. IEEE Access 8: 118396-118404 (2020)
• 
  Wei Wu, Biao Yang, Dong Wang, Weigong Zhang:
  A Novel Trajectory Generator Based on a Constrained GAN and a Latent Variables Predictor. IEEE Access 8: 212529-212540 (2020)
• 
  Si-Zhao Joe Qin, Yining Dong, Qinqin Zhu, Jin Wang, Qiang Liu:
  Bridging systems theory and data science: A unifying review of dynamic latent variable analytics and process monitoring. Annu. Rev. Control. 50: 29-48 (2020)
• 
  Hongbin Liu, Chong Yang, Mingzhi Huang, ChangKyoo Yoo:
  Soft sensor modeling of industrial process data using kernel latent variables-based relevance vector machine. Appl. Soft Comput. 90: 106149 (2020)
• 
  Afrah Shafquat, Ronald G. Crystal, Jason G. Mezey:
  Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes. BMC Bioinform. 21(1): 178 (2020)
• 
  Dong Hwi Jeong, Jong Min Lee:
  Ensemble learning based latent variable model predictive control for batch trajectory tracking under concept drift. Comput. Chem. Eng. 139: 106875 (2020)
• 
  Qinqin Zhu, Si-Zhao Joe Qin, Yining Dong:
  Dynamic latent variable regression for inferential sensor modeling and monitoring. Comput. Chem. Eng. 137: 106809 (2020)
• 
  Saeed Ghorbani, Calden Wloka, Ali Etemad, Marcus A. Brubaker, Nikolaus F. Troje:
  Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model. Comput. Graph. Forum 39(8): 225-239 (2020)
• 
  Ming Ouyang, Xin-Yuan Song:
  Bayesian Local Influence of Generalized Failure Time Models with Latent Variables and Multivariate Censored Data. J. Classif. 37(2): 298-316 (2020)
• 
  Jin-Chuan Duan, Andras Fulop, Yu-Wei Hsieh:
  Data-cloning SMC²: A global optimizer for maximum likelihood estimation of latent variable models. Comput. Stat. Data Anal. 143 (2020)
• 
  Xiaoqing Wang, Xiangnan Feng, Xinyuan Song:
  Joint analysis of semicontinuous data with latent variables. Comput. Stat. Data Anal. 151: 107005 (2020)
• 
  Hao-Tong Ye, Kai-Lin Lo, Shang-Yu Su, Yun-Nung Chen:
  Knowledge-Grounded Response Generation with Deep Attentional Latent-Variable Model. Comput. Speech Lang. 63: 101069 (2020)
• 
  Fatemeh Hosseini, Omid Karimi:
  Approximate likelihood inference in spatial generalized linear mixed models with closed skew normal latent variables. Commun. Stat. Simul. Comput. 49(1): 121-134 (2020)

skipping 1,027 more matches