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Variational Recurrent Auto-Encoders

arXiv 1412.6581 ↗First posted 20 Dec 2014stat.ML cs.LG cs.NEcited by 53

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Abstract (arXiv)

In this paper we propose a model that combines the strengths of RNNs and SGVB: the Variational Recurrent Auto-Encoder (VRAE). Such a model can be used for efficient, large scale unsupervised learning on time series data, mapping the time series data to a latent vector representation. The model is generative, such that data can be generated from samples of the latent space. An important contribution of this work is that the model can make use of unlabeled data in order to facilitate supervised training of RNNs by initialising the weights and network state.

Key facts. Cited by 53 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Dec 2014.

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Citing papers per year: 2021: 18; 2022: 8; 2023: 11; 2024: 6; 2025: 7; 2026: 3.

53 papers.

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  1. 2021TimeVAE: A Variational Auto-Encoder for Multivariate Time Series Generationcited by 139
  2. 2023Causal Recurrent Variational Autoencoder for Medical Time Series Generationcited by 44
  3. 2021Anomaly Detection of Time Series with Smoothness-Inducing Sequential Variational Auto-Encodercited by 39
  4. 2022Deep Latent State Space Models for Time-Series Generationcited by 37
  5. 2023Deep networks for system identification: a Surveycited by 35
  6. 2021Unsupervised Speech Enhancement using Dynamical Variational Auto-Encoderscited by 28
  7. 2021Towards Generating Real-World Time Series Datacited by 26
  8. 2021MaGNET: Uniform Sampling from Deep Generative Network Manifolds Without Retrainingcited by 23
  9. 2023Mixture of Soft Prompts for Controllable Data Generationcited by 23
  10. 2021Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural Activitycited by 18
  11. 2021Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Modelscited by 14
  12. 2022Recent Advances in Neural Text Generation: A Task-Agnostic Surveycited by 14
38 more
  1. 2021CausalMTA: Eliminating the User Confounding Bias for Causal Multi-touch Attributioncited by 12
  2. 2021Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel Machinecited by 11
  3. 2024Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Modelscited by 9
  4. 2023Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Modelscited by 7
  5. 2021Physics-based Differentiable Depth Sensor Simulationcited by 6
  6. 2021Multimodal Meta-Learning for Time Series Regressioncited by 6
  7. 2023Time-Transformer: Integrating Local and Global Features for Better Time Series Generation (Extended Version)cited by 6
  8. 2021Driving Style Representation in Convolutional Recurrent Neural Network Model of Driver Identificationcited by 5
  9. 2021Autoencoders as Tools for Program Synthesiscited by 4
  10. 2023Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenescited by 4
  11. 2024Generative Modeling of Neural Dynamics via Latent Stochastic Differential Equationscited by 4
  12. 2022A Survey on Artificial Intelligence for Music Generation: Agents, Domains and Perspectivescited by 3
  13. 2024Nonstationary Time Series Forecasting via Unknown Distribution Adaptationcited by 2
  14. 2021Generating Reliable Process Event Streams and Time Series Data based on Neural Networkscited by 1
  15. 2021Stochastic Recurrent Neural Network for Multistep Time Series Forecastingcited by 1
  16. 2022Neural Generalised AutoRegressive Conditional Heteroskedasticitycited by 1
  17. 2022Multi-Task Dynamical Systemscited by 1
  18. 2022Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generationcited by 1
  19. 2023Contrastive variational information bottleneck for aspect-based sentiment analysiscited by 1
  20. 2023Robust Multimodal Fusion for Human Activity Recognitioncited by 1
  21. 2023Learning Multimodal Latent Dynamics for Human-Robot Interactioncited by 1
  22. 2024Integrating Random Effects in Variational Autoencoders for Dimensionality Reduction of Correlated Datacited by 1
  23. 2025Synthetic Data Generation for Minimum-Exposure Navigation in a Time-Varying Environment using Generative AI Modelscited by 1
  24. 2025FairDRL-ST: Disentangled Representation Learning for Fair Spatio-Temporal Mobility Predictioncited by 1
  25. 2025Towards Comprehensive Information-theoretic Multi-view Learningcited by 1
  26. 2026Net-Ev2: A Generative Simulator for Network Event Evolutioncited by 1
  27. 2021A General Framework for Learning Prosodic-Enhanced Representation of Rap Lyricscited by 0
  28. 2021ProsoBeast Prosody Annotation Toolcited by 0
  29. 2021Anomaly Detection of Wind Turbine Time Series using Variational Recurrent Autoencoderscited by 0
  30. 2022Variational Heteroscedastic Volatility Modelcited by 0
  31. 2022Stain-Adaptive Self-Supervised Learning for Histopathology Image Analysiscited by 0
  32. 2023Speech representation learning: Learning bidirectional encoders with single-view, multi-view, and multi-task methodscited by 0
  33. 2023Variational Autoencoders for Noise Reduction in Industrial LLRF Systemscited by 0
  34. 2024RVRAE: A Dynamic Factor Model Based on Variational Recurrent Autoencoder for Stock Returns Predictioncited by 0
  35. 2024Rethinking Molecular Design: Integrating Latent Variable and Auto-Regressive Models for Goal Directed Generationcited by 0
  36. 2025Approximately Equivariant Recurrent Generative Models for Quasi-Periodic Time Series with a Progressive Training Schemecited by 0
  37. 20254TaStiC: Time and trend traveling time series clustering for classifying long-term type 2 diabetes patientscited by 0
  38. 2025Alternators With Noise Modelscited by 0

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