Auto-Encoding Variational Bayes
Diederik P. Kingma, Max Welling
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Citation edge evidence
- A survey on deep learning in medical image analysis→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Deep Reinforcement Learning: A Brief Survey→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Unsupervised Feature Learning via Non-parametric Instance Discrimination→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Recent Trends in Deep Learning Based Natural Language Processing [Review Article]→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Unsupervised Visual Representation Learning by Context Prediction→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- A review of uncertainty quantification in deep learning: Techniques, applications and cha…→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- On the Opportunities and Risks of Foundation Models→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Automatic differentiation in machine learning: a survey→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Review of Deep Learning Algorithms and Architectures→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervise…→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural…→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Deep Learning Applications in Medical Image Analysis→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Neural Architecture Search: A Survey→Auto-Encoding Variational BayesLegacy edge — source detail unavailable
- Auto-Encoding Variational Bayes→Stochastic variational inferenceLegacy edge — source detail unavailable
- Deep Learning Applications in Medical Image Analysis→A survey on deep learning in medical image analysisLegacy edge — source detail unavailable
- Unsupervised Feature Learning via Non-parametric Instance Discrimination→Unsupervised Visual Representation Learning by Context PredictionLegacy edge — source detail unavailable
- Review of Deep Learning Algorithms and Architectures→Deep Reinforcement Learning: A Brief SurveyLegacy edge — source detail unavailable
- Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep Learning→Stochastic variational inferenceLegacy edge — source detail unavailable
- Variational Inference: A Review for Statisticians→Stochastic variational inferenceLegacy edge — source detail unavailable
- A review of uncertainty quantification in deep learning: Techniques, applications and cha…→A survey on deep learning in medical image analysisLegacy edge — source detail unavailable
- A review of uncertainty quantification in deep learning: Techniques, applications and cha…→Dropout as a Bayesian Approximation: Representing Model Uncertainty in\n Deep LearningLegacy edge — source detail unavailable
- A review of uncertainty quantification in deep learning: Techniques, applications and cha…→Variational Inference: A Review for StatisticiansLegacy edge — source detail unavailable
- On the Opportunities and Risks of Foundation Models→Unsupervised Feature Learning via Non-parametric Instance DiscriminationLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Stochastic variational inference | 2013 | 1,480 |
What cites it, inside the corpus
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Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record
Topics
| Gaussian Processes and Bayesian Inference | Computer Science |
| Machine Learning and Algorithms | Computer Science |
| Bayesian Methods and Mixture Models | Computer Science |
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