Latent Variable Models

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9 papers in the last four weeks, up 50% on the four weeks before. 0.1% of all new papers.

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  1. Empirical Variational Autoencoder

    Oct 5, 2026Kaede ShioharaVariational AutoencodersLatent Variable Models

    The University of Tokyo

  2. Latent Similarity Gaussian Processes: A Theory-Grounded Approach to Personalized Suicide-Risk Forecasting for Clinical Decision-Support

    Oct 5, 2026Yaniv Yacoby, Weiwei Pan, Hope Neveux +4Latent Variable ModelsSuicide Risk Modeling

    Wellesley College · Harvard University · Harvard University Harvard Medical School Massachusetts General Hospital

  3. vMF Sentence LDA: A Spherical Topic Model over Sentence Embeddings

    Oct 4, 2026Ryotaro Kobayashi, Yuri Murayama, Kiyoshi IzumiLatent Variable ModelsTopic Modeling

    Graduate School of Engineering, The University of Tokyo, Tokyo, Japan

  4. Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models

    Oct 2, 2026Maksym Tretiakov, Sarah Filippi, Vincent Fortuin +3Latent Variable ModelsAmortized Inference

    LMU Munich · Munich Center for Machine Learning (MCML) · Imperial College London +3

  5. Predictive Self-Supervised Learning Provably Identifies Stochastic Signals under Nuisance

    Sep 29, 2026Fabian A. Mikulasch, Friedemann ZenkeLatent Variable ModelsRepresentation Identifiability

    Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland · Faculty of Science, University of Basel, Switzerland

  6. Generative Residual Factorization

    Sep 28, 2026Letian Gong, Yuzhou HongRepresentation CollapseLatent Variable Models

    Zhejiang University of Science and Technology · Zhejiang Sci-Tech University

  7. SLP-ProbHard: Probabilistic Hard-Constrained Learning via Structural Latent Parameterization

    Sep 27, 2026Wondesen Teshome Bekele, Marco D'OriaConstrained Generative ModelingLatent Variable Models

    Department of Engineering and Architecture, University of Parma, Parma, Italy · University School for Advanced Studies IUSS Pavia, Pavia, Italy

  8. Towards Identifiable Representations under Misspecified Structure

    Sep 27, 2026Yuke Li, Yujia Zheng, Ziyi Chen +2Latent Variable ModelsRepresentation Identifiability

    University of Maryland College Park, College Park, MD, USA · Carnegie Mellon University, Pittsburgh PA, USA

  9. Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation

    Sep 21, 2026Jurij Schönfeld, Tom Beucler, Julien Savre +2Latent Variable ModelsClimate Modeling

    Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany · University of Bremen, Institute of Environmental Physics (IUP), Bremen, Germany · Faculty of Geosciences and Environment, University of Lausanne, Lausanne, Switzerland +3

  10. Hessian Rank Constraint for Learning Structure of Nonlinear Latent Variable Models

    Sep 21, 2026Zijian Li, Ruichu Cai, Feng Xie +7Latent Variable ModelsCausal Discovery

    Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE · Carnegie Mellon University, Pittsburgh, PA, USA · Guangdong University of Technology, Guangzhou, China +3

  11. A Closed-Form Estimator and Diagnostic Battery for Anchor-Judge Error Correlation, Under a Single-Common-Factor Model

    Sep 8, 2026Veerendra Kumar SunkavalliLatent Variable ModelsLLM-as-a-Judge

    Independent Researcher

  12. Towards unsupervised representation learning for quantum data: quantum models with inference and generation

    Aug 31, 2026Robin Lorenz, Eric Brunner, Marcello BenedettiLatent Variable ModelsQuantum Generative Modeling

    Quantinuum, London, United Kingdom

  13. When Can We Work in Embedding Space? What Text Embeddings Preserve

    Aug 31, 2026Simon FreyaldenhovenText EmbeddingsLatent Variable Models

    Federal Reserve Bank of Philadelphia

  14. A Deep Latent Variable Framework for Jointly Modeling Missingness, Measurement Error, and Heterogeneity

    Aug 30, 2026Yasin Khadem Charvadeh, Grace Y. Yi, Mithat Gönen +1Variational AutoencodersIncomplete Data Imputation

    Department of Radiology and Diagnostic Imaging, University of Alberta, Edmonton, Alberta, Canada · Department of Statistical and Actuarial Sciences, Department of Computer Science, University of Western Ontario, Ontario, Canada · Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA +1

  15. Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

    Aug 18, 2026Naoki Egami, Sooahn ShinSemiparametric InferenceLatent Variable Models

    Department of Political Science and Statistics and Data Science Center, Massachusetts Institute of Technology, Cambridge, MA 02139 · Department of Political Science, Massachusetts Institute of Technology, Cambridge, MA 02139

  16. Latent variable models for simultaneous EOV identification and removal in population-based SHM

    Aug 12, 2026M. D. Champneys, M. R. Jones, A. J. Hughes +3Latent Variable ModelsStructural Health Monitoring

    Dynamics Research Group, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK · Centre for Machine Intelligence, University of Sheffield, Mappin Street, Sheffield S1 3JD, UK

  17. When Is a General Factor Distinguishable? Non-Proportionality, Stable Structure, and the Bifactor Decision

    Aug 11, 2026Jinsong ChenLatent Variable ModelsParameter Identifiability

    Faculty of Education, The University of Hong Kong

  18. Marginal Matching Does Not License Factorized Sampling: Auditing Conditional Style Leakage in Factorized Generative Models

    Aug 5, 2026Duong Bach, Hai Nguyen Hong, Cuong DoDisentangled Representation LearningLatent Variable Models

    Smart Health Center (VISHC), VinUniversity, Ha Noi, Viet Nam

  19. UNVaMP: Neural Knowledge Tracing with Variational Regularization of Latent Knowledge Dynamics

    Aug 4, 2026Carson J. Cook, Ahmed J. Zerouali, Anthony Schmidt +3Latent Variable ModelsInterpretable ML

    Amplify Education, Inc.

  20. Conditionally Identifiable Latent-Environment Modeling for Out-of-Distribution Recommendation

    Aug 4, 2026Qianqian Wang, Wenwu Gong, Yunshan Li +3Latent Variable ModelsOOD Generalization

    Shenzhen Key Laboratory of Safety and Security for Next Generation of Industrial Internet, Southern University of Science and Technology, Shenzhen, China · Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China · School of Mathematical and Computational Sciences, Massey University, Auckland, New Zealand

  21. DAIF: A Data-Driven Intermediate Fusion Framework for Multimodal Supervised Learning via Approximate Message Passing

    Aug 3, 2026Sagnik Nandy, Samriddha Lahiry, Pragya Sur +1Latent Variable ModelsMultimodal Fusion

    Ohio State University · National University of Singapore · Harvard University

  22. Learning Latent Reasoning Traces for Scalar Reward Models End-to-End

    Jul 31, 2026Sanwoo Lee, Clive Bai, Hsiu-Yuan Huang +3Reward ModelingLLM Alignment

    National Key Laboratory for Multimedia Information Processing, Peking University · School of Computer Science, Peking University · LLM Department, Tencent

  23. Latent-Kernel Discrete Flow Maps for Few-Step Generation

    Jul 29, 2026Mansoor Ahmed, Yue-Tsz Fan, Hemanth Venkateswara +1Latent Variable ModelsFew-Step Diffusion Sampling

    Georgia State University, Atlanta, GA, USA · Georgia Institute of Technology, Atlanta, GA, USA

  24. Beyond ICA: Identifiability by Symmetry Breaking

    Jul 25, 2026Pengzhou WuLatent Variable ModelsRepresentation Identifiability

    SANKEN, University of Osaka

  25. RAMP: Recognition parametrisation by Amortised Message Passing

    Jul 21, 2026Lior Fox, Kai Biegun, James Heald +3Unsupervised LearningLatent Variable Models

    1Gatsby Computational Neuroscience Unit · Centre for Artificial Intelligence University College London

  26. Unveiling Invariant and Transferable Latent Factors Across Heterogeneous Environments via ATLAS

    Jul 20, 2026Yihong Gu, Katherine Liao, Tianxi CaiLatent Variable ModelsDomain Generalization

    Harvard University

  27. An efficient adaptive dimension selection algorithm for multidimensional probit graded response models

    Jul 20, 2026Yu Zhou, Yincai Tang, Bin Lv +1Latent Variable ModelsBayesian Inference

    1KLATASDS-MOE 1School of Statistics, East China Normal University, Shanghai, 200062, China · 2Zhiyuan School of Liberal Arts,Beijing Institute of Petrochemical Technology,Beijing 102617, China

  28. Coordinated Disentanglement with Iterative Mode Discovery Under Hidden Correlations

    Jul 19, 2026Rong Hu, Ling ChenDisentangled Representation LearningLatent Variable Models

    State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China · College of Computer Science and Technology, Zhejiang University, Hangzhou, China

  29. What does a Bayes-filtered transformer believe? A predictive Monte Carlo approach

    Jul 19, 2026Afiq Abdillah Effiezal Aswadi, Haotong Ma, Susan WeiTransformer InterpretabilityLatent Variable Models

    Department of Econometrics and Business Statistics Monash University

  30. Partially Correlated Verifier Cascades in LLM Harnesses: Concave Log-Odds, Polynomial Reliability, and Blind-Spot Ceilings

    Jul 15, 2026Jiangang HanLatent Variable ModelsLLM Answer Verification

    Independent researcher

  31. The Hyperspherical Geometry of CLIP Latent Space: A Semantic Mixture Model

    Jul 15, 2026Zijie Yu, Gaowen Liu, Ramana Rao Kompella +2Latent Variable ModelsHyperspherical Representation Learning

    Tsinghua University · Cisco Research · University of Illinois Chicago

  32. The Spectral Structure of Latent Treatment Effects

    Jul 12, 2026Hamza Virk, Bijan Mazaheri, Yihren WuCausal Effect EstimationLatent Variable Models

    1Dartmouth College · 2Broad Institute of MIT and Harvard · 3Hofstra University

  33. CASL-VAE: Learning Structured Latent Variables from Unpaired Data for Semi-supervised Clustering and Paired Sample Generation

    Jul 9, 2026Sai Spandana Chintapalli, Pratik Chaudhari, Christos DavatzikosVariational AutoencodersContrastive Learning

    Center for AI and Data Science for Integrated Diagnostics, University of Pennsylvania · Department of Bioengineering, University of Pennsylvania · Department of Electrical and Systems Engineering, University of Pennsylvania +1

  34. Recovering Latent Structures after Variational Bayesian Variable Selection: Fit Assessment and Factor-Number Selection in Partially Exploratory Factor Analysis

    Jul 8, 2026Jinsong Chen, Yi JinLatent Variable Models

    Faculty of Education The University of Hong Kong · Department of Curriculum and Instruction The Education University of Hong Kong

  35. FedSPM: Routing-Enabled Federated Learning under Dual Heterogeneity via Semiparametric Mixture

    Jul 5, 2026Zijian Wang, Pengfei Li, Guangyu Yang +1Latent Variable ModelsAdaptive Model Routing

    Institute of Statistics and Big Data, Renmin University of China · Department of Statistics and Actuarial Science, University of Waterloo

  36. Poisson-Gamma Modeling of Inter-Relational Dependencies in Dynamic Knowledge Graphs

    Jul 3, 2026Nan Fang, Yijun Wang, Hao Liao +1Latent Variable ModelsTemporal Link Prediction

    School of Computing and Information Technology, Great Bay University, Dongguan, Guangdong, China · Tsinghua University, Shenzhen, Guangdong, China · College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, Guangdong, China +1

  37. From Structural Equation Modelling to Double Machine Learning: Robustness Analysis for Survey-Based Research

    Jul 1, 2026Ka Ching Chan, Qiana Liu, Sanjib Tiwari +1Double MLLatent Variable Models

    School of Business, Law, Humanities and Pathways, University of Southern Queensland, Springfield, 4300, Queensland, Australia

  38. Perspectives on Latent Factor Indeterminacy and its Implications for Data Representation

    Jun 27, 2026Carel F. W. PeetersRepresentation LearningLatent Variable Models

    Mathematical & Statistical Methods group – Biometris, Wageningen University & Research

  39. RetiSEM: Generalising Causal Models for Fragmented Biomedical Data

    Jun 23, 2026Inam Ullah, Imran Razzak, Shoaib JameelLatent Variable ModelsStructural Causal Models

    University of Southampton, Southampton, SO18 1PB, Hampshir, United Kingdom · Mohamed bin Zayed University of Artificial Intelligence, United Arab Emirates

  40. FLFL: Federated Latent Factor Learning for Private Recovery of Spatio-Temporal Signals

    Jun 22, 2026Chengjun Yu, Di Wu, Yi He +1Latent Variable ModelsPrivacy-Preserving ML

    Southwest University Chongqing, China · College of William & Mary Williamsburg, Virginia, United States · Beihang University Beijing, China

  41. Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability

    Jun 19, 2026Mathieu Cyrille Simon, Pascal Frossard, Christophe De VleeschouwerUnsupervised LearningDisentangled Representation Learning

    1UCLouvain, ICTEAM, Louvain-la-Neuve, Belgium · 2EPFL, LTS4 laboratory, Lausanne, Switzerland.

  42. Shrinkage priors for Bayesian Substitute Confounders

    Jun 16, 2026Yordan P. Raykov, Hengrui Luo, Justin D. Strait +1Causal Effect EstimationLatent Variable Models

    School of Mathematical Sciences, University of Nottingham, Nottingham, UK · Department of Statistics, Rice University, USA · Lawrence Berkeley National Laboratory, USA +1

  43. Concept Modulation Models: A Unified Framework for Identifiability and Extrapolation

    Jun 16, 2026Soheun Yi, Yizhou Lu, Chandler Squires +1Latent Variable ModelsGenerative Modeling

    Department of Statistics and Data Science, Carnegie Mellon University · Machine Learning Department, Carnegie Mellon University

  44. Information Gap and Feasibility-Aware Inference in Binomial Logistic Mixtures

    Jun 14, 2026Yuta Hayashida, Shonosuke SugasawaLatent Variable Models

    Graduate School of Economics, Keio University · Faculty of Economics, Keio University

  45. Structured Nonparametric Variational Inference for Dependent Latent Modeling

    Jun 13, 2026Yuda Shao, Zhiling Gu, Shan YuLatent Variable ModelsVariational Inference

    Department of Statistics, University of Virginia · Department of Biostatistics, Yale University

  46. Zero-Inflated Gaussian Distributions Enable Parameter-Space Sparsity in Estimation-of-Distribution Algorithms

    Jun 11, 2026Andreas Faust, Sven Nitzsche, Juergen BeckerStochastic OptimizationParameter Estimation

    University of Freiburg, Freiburg, Germany · FZI Research Center for Information Technology, Karlsruhe, Germany · Karlsruhe Institute of Technology, Karlsruhe, Germany

  47. Generative Modeling of Bach-Style Symbolic Music: A Comparative Study of Autoregressive, Latent-Variable, and Adversarial Approaches

    Jun 11, 2026Dezhi Yu, Kyuil Lee, Yongkang HuangVariational AutoencodersLatent Variable Models

  48. Simultaneous Latent Budget Trees for Stratified Classification

    Jun 11, 2026Cristian Buoncompagni, Stefano Pellegrino, Giulia Vannucci +2Latent Variable ModelsInterpretable ML

    Department of Physics, University of Naples Federico II, via Cintia 21, Napoli, 80125, Italy. · Department of Electrical Engineering and Information Technologies, University of Naples Federico II, via Claudio 21, Napoli, 80125, Italy. · Department of Neuroscience, Reproductive Sciences and Odontostomatology, University of Naples Federico II, via Sergio Pansini 5, Napoli, 80131, Italy.

  49. Identifiability Without Gaussianity: Symbolic World Models and Near-Infinite Temporal Consistency

    Jun 9, 2026Seth Dobrin, Łukasz ChmielLatent Variable ModelsCausal Representation Learning

    1ARYA Labs, PBC

  50. Machine Learning Methods for Studying Latent Neural Activity Dynamics

    Jun 9, 2026Shufeng Kong, Fumei Deng, Xinyi Dong +7Dynamical SystemsLatent Variable Models

    School of Software Engineering, Sun Yat-sen University, Zhuhai, China · School of Computer Science and Artificial Intelligence, Foshan University, Foshan, China · Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA +2

  51. Identifiability and Estimation for Unlabeled Finite Mixtures under Marginal Independence

    Jun 6, 2026Takafumi Kanamori, Yushi Hirose, Shohei YamamotoLatent Variable ModelsParameter Identifiability

    Department of Mathematical and Computing Science, Institute of Science Tokyo · RIKEN Center for Advanced Intelligence Project

  52. Generative Modeling of Discrete Latent Structures via Dynamic Policy Gradients

    Jun 5, 2026Stefan Ivanovic, Ge Liu, Mohammed El-KebirLatent Variable ModelsPolicy Gradient Methods

    Siebel School of Computing and Data Science, University of Illinois at Urbana-Champaign, IL 61801, USA · Cancer Center at Illinois, University of Illinois Urbana-Champaign, IL 61801, USA

  53. Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference

    Jun 4, 2026Shengxian Ding, Haonan Gao, Pangpang Liu +2Latent Variable ModelsBayesian Inference

    Department of Biostatistics, Yale University, New Haven, USA

  54. Gaussian Process Latent Factor Regression for Low-Data, High-Dimensional Output Problems

    Jun 4, 2026Edward T. Stevenson, Eric T. Wolf, Mei Ting Mak +2Latent Variable ModelsDimensionality Reduction

    University of Cambridge · University of Colorado Boulder · University of Oxford +1

  55. Non-Negative Matrix Factorization for Event Data

    Jun 4, 2026Raphaël RomeroTemporal Point ProcessesLatent Variable Models

    Ghent University · Ghent, Belgium

  56. Environment-Robust Representation Learning with Empirical Bayes

    Jun 3, 2026Yuli Slavutsky, Matthew Shen, Bohan Wu +1Latent Variable ModelsEmpirical Bayes

    Department of Statistics Columbia University New York, NY 10027, USA · Departments of Statistics and Computer Science Columbia University New York, NY 10027, USA

  57. An Ensembled Latent Factor Model via Differential Evolution and Gradient Descent Optimization

    Jun 3, 2026Rui Zhang, Jinhang Liu, Wenbo ZhangRepresentation LearningLatent Variable Models

    Chongqing Academy of Economics Research Chongqing, China · College of Computer and Information Science, Southwest University Chongqing, China

  58. Network Learning with Semi-relaxed Gromov-Wasserstein

    Jun 1, 2026Charles Dufour, Ulysse Naepels, Leonardo V. SantoroGraph Structure LearningLatent Variable Models

    EPFL, Institute of Mathematics Lausanne, Switzerland

  59. VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting

    Jun 1, 2026Xudong Zhang, Jierui Lei, Jiacheng Li +3Multivariate Time Series ForecastingLatent Variable Models

    School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China. · Center for Machine Learning Research, Peking University, Beijing, China. · Amap, Alibaba Group, China. +2

  60. Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo

    May 29, 2026Xiaoyu Wang, Jonathan H. HugginsMarkov Chain Monte CarloStochastic Gradient Langevin Dynamics

    Department of Mathematics & Statistics, Boston University · Faculty of Computing & Data Sciences, Boston University