Towards Bayesian Deep Learning: A Survey
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Summary
A general introduction to Bayesian deep learning is provided and its recent applications on recommender systems, topic models, and control are reviewed.
- Type
- preprint
- Published
- 2016-04-06
- Cited by
- 50
- References
- 94
- Access
- Open access
- OpenAlex
- https://openalex.org/W2338752163
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:8604408
Keywords
Artificial intelligence, Inference, Computer science, Deep learning, Machine learning
References
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- A Recurrent Latent Variable Model for Sequential Data
- Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
- Relational Stacked Denoising Autoencoder for Tag Recommendation
- Pattern Recognition and Machine Learning
- An Introduction to Variational Methods for Graphical Models
- Relation regularized matrix factorization
- Bayesian dark knowledge
- Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks
- Continuous Time Dynamic Topic Models
- Auto-Encoding Variational Bayes
- Matrix Variate Distributions
- A Guide to Distribution Theory and Fourier Transforms
- The Adaptive Clustering Method for the Long Tail Problem of Recommender Systems
- Forecasting, Structural Time Series Models and the Kalman Filter
- Cross-Space Affinity Learning with Its Application to Movie Recommendation
- Auto-association by multilayer perceptrons and singular value decomposition
- Deep Collaborative Filtering via Marginalized Denoising Auto-encoder
- Product of Gaussians for speech recognition
- Keeping the neural networks simple by minimizing the description length of the weights
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- Unsupervised Machine Learning for Networking: Techniques, Applications and Research Challenges
- Learning from Few Samples with Memory Network
- Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
- Learning Non-Linear Functions for Text Classification
- Investigations of neural attractor dynamics in human visual awareness
- Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices
- Asking 'Why' in AI: Explainability of intelligent systems - perspectives and challenges
- Concept-Oriented Deep Learning
- Quelle transparence pour les algorithmes d'apprentissage machine ?
- The Relevance of Bayesian Layer Positioning to Model Uncertainty in Deep Bayesian Active Learning
- Predictive large reaction network modeling via data-driven methods: application to biomass conversion
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- Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI
- A Probabilistic Learning Approach to UWB Ranging Error Mitigation
- Machine learning technology in the application of genome analysis: A systematic review.
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