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Publication search results
found 1,484 matches
- 2024
- Junyao You, Chengpu Yu:
Sparse plus low-rank identification for dynamical latent-variable graphical AR models. Autom. 159: 111405 (2024) - Melpomeni Kasapi, Kexin Xu, Timothy M. D. Ebbels, Declan P. O'Regan, James S. Ware, Joram M. Posma:
LAVASET: Latent Variable Stochastic Ensemble of Trees. An ensemble method for correlated datasets with spatial, spectral, and temporal dependencies. Bioinform. 40(3) (2024) - Aditi Jha, Zoe C. Ashwood, Jonathan W. Pillow:
Active Learning for Discrete Latent Variable Models. Neural Comput. 36(3): 437-474 (2024) - Luca Brusa, Fulvia Pennoni, Francesco Bartolucci:
Maximum likelihood estimation for discrete latent variable models via evolutionary algorithms. Stat. Comput. 34(1): 62 (2024) - Laixu Shang, Qian-Zhen Zheng, Ping-Feng Xu, Na Shan, Man-Lai Tang:
A generalized expectation model selection algorithm for latent variable selection in multidimensional item response theory models. Stat. Comput. 34(1): 49 (2024) - Zhiyong Hu, Chao Wang, Jianguo Wu, Dongping Du:
Gaussian Process Latent Variable Model-Based Multi-Output Modeling of Incomplete Data. IEEE Trans Autom. Sci. Eng. 21(2): 1941-1951 (2024) - Xu Chen, Xiao He, Si-Zhao Joe Qin:
Bidirectional Dynamic Latent Variable Analysis for Closed-Loop Process Monitoring. IEEE Trans. Ind. Electron. 71(8): 9823-9833 (2024) - Yuchen He, Zhangjie Guan, Jun Wang:
Virtual Sensing Techniques for Nonstationary Processes Based on a Multirate Probabilistic Dual-Latent-Variable Supervised Slow Feature Analysis. IEEE Trans. Ind. Informatics 20(3): 4884-4893 (2024) - Di Wang, Yuhui Wang, Xiaochen Xian:
A Latent Variable-Based Multitask Learning Approach for Degradation Modeling of Machines With Dependency and Heterogeneity. IEEE Trans. Instrum. Meas. 73: 1-15 (2024) - Xiaoying Tan, Wei Guo, Ranran Liu, Tianhong Pan:
A data-driven soft-sensing approach using probabilistic latent variable model with functional data framework. Trans. Inst. Meas. Control 46(5): 913-926 (2024) - Wei Chen, Zhiyi Huang, Ruichu Cai, Zhifeng Hao, Kun Zhang:
Identification of Causal Structure with Latent Variables Based on Higher Order Cumulants. AAAI 2024: 20353-20361 - Debo Cheng, Ziqi Xu, Jiuyong Li, Lin Liu, Jixue Liu, Wentao Gao, Thuc Duy Le:
Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders. AAAI 2024: 11480-11488 - Zhi Liu, Sarah Rankin, Nikhil Garg:
Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling. AAAI 2024: 22258-22265 - Aravind Venugopal, Stephanie Milani, Fei Fang, Balaraman Ravindran:
MABL: Bi-Level Latent-Variable World Model for Sample-Efficient Multi-Agent Reinforcement Learning. AAMAS 2024: 1865-1873 - Phuong Nguyen, Tuan M. V. Le:
SeeM: A Shared Latent Variable Model for Unsupervised Multi-view Anomaly Detection. PAKDD (1) 2024: 78-90 - Hu Hu, Sabato Marco Siniscalchi, Chin-Hui Lee:
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori. CoRR abs/2401.13766 (2024) - Navid Ziaei, Behzad Nazari, Ali Yousefi:
A Discriminative Bayesian Gaussian Process Latent Variable Model for High-Dimensional Data. CoRR abs/2401.16497 (2024) - Sandipp Krishnan Ravi, Yigitcan Comlek, Wei Chen, Arjun Pathak, Vipul Gupta, Rajnikant Umretiya, Andrew Hoffman, Ghanshyam Pilania, Piyush Pandita, Sayan Ghosh, Nathaniel Mckeever, Liping Wang:
Interpretable Multi-Source Data Fusion Through Latent Variable Gaussian Process. CoRR abs/2402.04146 (2024) - Deqian Kong, Dehong Xu, Minglu Zhao, Bo Pang, Jianwen Xie, Andrew Lizarraga, Yuhao Huang, Sirui Xie, Ying Nian Wu:
Latent Plan Transformer: Planning as Latent Variable Inference. CoRR abs/2402.04647 (2024) - Maksim Sinelnikov, Manuel Haussmann, Harri Lähdesmäki:
Latent variable model for high-dimensional point process with structured missingness. CoRR abs/2402.05758 (2024) - Marvin Wyrich, Marvin Muñoz Barón, Justus Bogner:
Apples, Oranges, and Software Engineering: Study Selection Challenges for Secondary Research on Latent Variables. CoRR abs/2402.08706 (2024) - James Odgers, Chrysoula Kappatou, Ruth Misener, Sarah Filippi:
Mixed-Output Gaussian Process Latent Variable Models. CoRR abs/2402.09122 (2024) - Sayed Sajad Hashemi, Michael Guerzhoy, Noah H. Paulson:
Toward Learning Latent-Variable Representations of Microstructures by Optimizing in Spatial Statistics Space. CoRR abs/2402.11103 (2024) - Anirudh Prabhakaran, YeKun Xiao, Ching-Yu Cheng, Dianbo Liu:
Improve Robustness of Eye Disease Detection by including Learnable Probabilistic Discrete Latent Variables into Machine Learning Models. CoRR abs/2402.16865 (2024) - Marco Zaffalon, Alessandro Antonucci:
A Note on Bayesian Networks with Latent Root Variables. CoRR abs/2402.17087 (2024) - Nathan Mankovich, Homer Durand, Emiliano Diaz, Gherardo Varando, Gustau Camps-Valls:
Recovering Latent Confounders from High-dimensional Proxy Variables. CoRR abs/2403.14228 (2024) - Adam Karvonen:
Emergent World Models and Latent Variable Estimation in Chess-Playing Language Models. CoRR abs/2403.15498 (2024) - 2023
- Matthieu Puigt:
Méthodes d'analyse en variables latentes fondées sur la parcimonie et/ou la faiblesse de rang. Application aux problèmes inverses multivariés. University of the Littoral Opal Coast, Dunkerque, France, 2023 - Théo Galy-Fajou:
Latent variable augmentation for approximate Bayesian inference: applications for Gaussian processes. Technical University of Berlin, Germany, 2023 - Yun Wang, Ze Ying, Yuchen He:
A Quality-Related Concurrent Dual-Latent Variable Model and Its Semi-Supervised Soft Sensor Applications. IEEE Access 11: 47539-47551 (2023)
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