• 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 77 matches

• 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)
• 
  Xiaoqing Wang, Xiangnan Feng, Xinyuan Song:
  Joint analysis of semicontinuous data with latent variables. Comput. Stat. Data Anal. 151: 107005 (2020)
• 
  Beau Dabbs, Samrachana Adhikari, Tracy M. Sweet:
  Conditionally Independent Dyads (CID) network models: A latent variable approach to statistical social network analysis. Soc. Networks 63: 122-133 (2020)
• 
  Mehran Safayani, Saeid Momenzadeh, Abdolreza Mirzaei, Masoomeh Sadat Razavi:
  A latent variable model for two-dimensional canonical correlation analysis and the variational inference. Soft Comput. 24(12): 8737-8749 (2020)
• 
  Yining Dong, Yingxiang Liu, Si-Zhao Joe Qin:
  Efficient Dynamic Latent Variable Analysis for High-Dimensional Time Series Data. IEEE Trans. Ind. Informatics 16(6): 4068-4076 (2020)
• 
  Chao Chen, Fei Shen, Jiawen Xu, Ruqiang Yan:
  Probabilistic Latent Semantic Analysis-Based Gear Fault Diagnosis Under Variable Working Conditions. IEEE Trans. Instrum. Meas. 69(6): 2845-2857 (2020)
• 
  Anh-Huy Phan, Andrzej Cichocki, Ivan V. Oseledets, Giuseppe Giovanni Calvi, Salman Ahmadi-Asl, Danilo P. Mandic:
  Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition. IEEE Trans. Neural Networks Learn. Syst. 31(6): 2174-2188 (2020)
• 
  Anh-Huy Phan, Andrzej Cichocki, André Uschmajew, Petr Tichavský, George Luta, Danilo P. Mandic:
  Tensor Networks for Latent Variable Analysis: Novel Algorithms for Tensor Train Approximation. IEEE Trans. Neural Networks Learn. Syst. 31(11): 4622-4636 (2020)
• 
  Hao Xiong, Shlomo Berkovsky, Roneel V. Sharan, Sidong Liu, Enrico W. Coiera:
  Robust Vision-Based Workout Analysis Using Diversified Deep Latent Variable Model. EMBC 2020: 2155-2158
• 
  Lin Qiu, Vernon M. Chinchilli, Lin Lin:
  Deep Latent Variable Model for Longitudinal Group Factor Analysis. CoRR abs/2005.05210 (2020)
• 2019
• 
  Shota Harada, Hideaki Hayashi, Seiichi Uchida:
  Biosignal Generation and Latent Variable Analysis With Recurrent Generative Adversarial Networks. IEEE Access 7: 144292-144302 (2019)
• 
  Ye-mao Xia, Nian-Sheng Tang:
  Bayesian analysis for mixture of latent variable hidden Markov models with multivariate longitudinal data. Comput. Stat. Data Anal. 132: 190-211 (2019)
• 
  Deepak Sharma, Pravin Chandra:
  Identification of latent variables using, factor analysis and multiple linear regression for software fault prediction. Int. J. Syst. Assur. Eng. Manag. 10(6): 1453-1473 (2019)
• 
  Shota Harada, Hideaki Hayashi, Seiichi Uchida:
  Biosignal Generation and Latent Variable Analysis with Recurrent Generative Adversarial Networks. CoRR abs/1905.07136 (2019)
• 2018
• 
  Jacob Gray:
  The Use of Discrete Latent Variables in Dyadic Data Analysis. University of California, Riverside, USA, 2018
• 
  Johannes Leder, Jan A. Häusser, Stefan Krumm, Markus Germar, Alexander Schlemmer, Stefan Kaiser, Annemarie Kalis, Andreas Mojzisch:
  The Cognitive Underpinnings of Option Generation in Everyday Life Decision-Making: A Latent Variable Analysis. Cogn. Sci. 42(8): 2562-2591 (2018)
• 
  Vardan Papyan, Ronen Talmon:
  Multimodal latent variable analysis. Signal Process. 142: 178-187 (2018)
• 
  Kelly Trezise, Robert A. Reeve:
  Patterns of anxiety in algebraic problem solving in Australian adolescents: A three-step latent variable analysis. CogSci 2018
• 
  Hernán F. García, Álvaro Ángel Orozco, Mauricio A. Álvarez:
  Nonlinear Probabilistic Latent Variable Models for Groupwise Correspondence Analysis in Brain Structures. MLSP 2018: 1-6
• 
  Yannick Deville, Sharon Gannot, Russell Mason, Mark D. Plumbley, Dominic Ward:
  Latent Variable Analysis and Signal Separation - 14th International Conference, LVA/ICA 2018, Guildford, UK, July 2-5, 2018, Proceedings. Lecture Notes in Computer Science 10891, Springer 2018, ISBN 978-3-319-93763-2 [contents]
• 
  Anh Huy Phan, Andrzej Cichocki, Ivan V. Oseledets, Salman Ahmadi-Asl, Giuseppe Giovanni Calvi, Danilo P. Mandic:
  Tensor Networks for Latent Variable Analysis: Higher Order Canonical Polyadic Decomposition. CoRR abs/1809.00535 (2018)
• 
  Cédric Beaulac, Jeffrey S. Rosenthal, David Hodgson:
  A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis. CoRR abs/1811.12323 (2018)
• 2017
• 
  Robert Walecki, Ognjen Rudovic, Vladimir Pavlovic, Maja Pantic:
  Variable-state Latent Conditional Random Field models for facial expression analysis. Image Vis. Comput. 58: 25-37 (2017)
• 
  Etienne R. Ackermann, Caleb Kemere, Kourosh Maboudi, Kamran Diba:
  Latent variable models for hippocampal sequence analysis. ACSSC 2017: 724-728
• 
  Liz Amos, Satyajeet Raje, Masato Kimura, Preeti G. Kochar, Victoria Wilder, Ben Busby:
  Harmonizing User-defined Phenotypic Variables using Latent Semantic Analysis (LSA) to Improve Data Discoverability in dbGaP. AMIA 2017
• 
  Diego García, Ignacio Díaz Blanco, Daniel Pérez, Abel Alberto Cuadrado Vega, Manuel Domínguez-González:
  Latent variable analysis in hospital electric power demand using non-negative matrix factorization. ESANN 2017
• 
  Vincent Vigneron, Leonardo Tomazeli Duarte:
  Toward Rank Disaggregation: An Approach Based on Linear Programming and Latent Variable Analysis. LVA/ICA 2017: 192-200
• 
  Petr Tichavský, Massoud Babaie-Zadeh, Olivier J. J. Michel, Nadège Thirion-Moreau:
  Latent Variable Analysis and Signal Separation - 13th International Conference, LVA/ICA 2017, Grenoble, France, February 21-23, 2017, Proceedings. Lecture Notes in Computer Science 10169, 2017, ISBN 978-3-319-53546-3 [contents]
• 
  Mehran Safayani, Saeid Momenzadeh:
  A Latent Variable Model for Two-Dimensional Canonical Correlation Analysis and its Variational Inference. CoRR abs/1708.01519 (2017)
• 
  Alexander A. Alemi, Ben Poole, Ian Fischer, Joshua V. Dillon, Rif A. Saurous, Kevin Murphy:
  An Information-Theoretic Analysis of Deep Latent-Variable Models. CoRR abs/1711.00464 (2017)

skipping 47 more matches