mlsanityData to 14 Oct 2026

Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance

arXiv 1805.10407 ↗First posted 26 May 2018cs.LG cs.AI stat.MLcited by 34

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Abstract (arXiv)

Large amounts of labeled data are typically required to train deep learning models. For many real-world problems, however, acquiring additional data can be expensive or even impossible. We present semi-supervised deep kernel learning (SSDKL), a semi-supervised regression model based on minimizing predictive variance in the posterior regularization framework. SSDKL combines the hierarchical representation learning of neural networks with the probabilistic modeling capabilities of Gaussian processes. By leveraging unlabeled data, we show improvements on a diverse set of real-world regression tasks over supervised deep kernel learning and semi-supervised methods such as VAT and mean teacher adapted for regression.

Key facts. Cited by 34 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 May 2018.

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Citing papers per year: 2021: 6; 2022: 10; 2023: 8; 2024: 2; 2025: 6; 2026: 2.

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  1. 2022USB: A Unified Semi-supervised Learning Benchmark for Classificationcited by 95
  2. 2021Extending the WILDS Benchmark for Unsupervised Adaptationcited by 86
  3. 2021High-Dimensional Bayesian Optimisation with Variational Autoencoders and Deep Metric Learningcited by 54
  4. 2022Pre-Train Your Loss: Easy Bayesian Transfer Learning with Informative Priorscited by 43
  5. 2022NP-Match: When Neural Processes meet Semi-Supervised Learningcited by 25
  6. 2022Improved Training of Physics-Informed Neural Networks with Model Ensemblescited by 19
  7. 2022FisherMatch: Semi-Supervised Rotation Regression via Entropy-based Filteringcited by 16
  8. 2023Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networkscited by 16
  9. 2023Semi-Supervised Graph Imbalanced Regressioncited by 14
  10. 2022MMD-B-Fair: Learning Fair Representations with Statistical Testingcited by 13
  11. 2023PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidancecited by 9
  12. 2021Twin Neural Network Regression is a Semi-Supervised Regression Algorithmcited by 6
22 more
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  2. 2025Taste More, Taste Better: Diverse Data and Strong Model Boost Semi-Supervised Crowd Countingcited by 5
  3. 2021Semi-supervised Learning for Data-driven Soft-sensing of Biological and Chemical Processescited by 3
  4. 2022Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimationcited by 3
  5. 2021A lightweight deep learning based cloud detection method for Sentinel-2A imagery fusing multi-scale spectral and spatial featurescited by 2
  6. 2024Learning Representations for Independence Testingcited by 2
  7. 2025Natural Evolutionary Search meets Probabilistic Numericscited by 2
  8. 2022Consecutive Knowledge Meta-Adaptation Learning for Unsupervised Medical Diagnosiscited by 1
  9. 2023NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learningcited by 1
  10. 2023Mixed Semi-Supervised Generalized-Linear-Regression with Applications to Deep-Learning and Interpolatorscited by 1
  11. 2021Built Year Prediction from Buddha Face with Heterogeneous Labelscited by 0
  12. 2022A Generalized Weighted Optimization Method for Computational Learning and Inversioncited by 0
  13. 2022Deep Low-Density Separation for Semi-Supervised Classificationcited by 0
  14. 2023Regression with Sensor Data Containing Incomplete Observationscited by 0
  15. 2023An information-Theoretic Approach to Semi-supervised Transfer Learningcited by 0
  16. 2024Exploring Probabilistic Models for Semi-supervised Learningcited by 0
  17. 2025Toward Robust Semi-supervised Regression via Dual-stream Knowledge Distillationcited by 0
  18. 2025Unbiased Stochastic Optimization for Gaussian Processes on Finite Dimensional RKHScited by 0
  19. 2025Response to Promises and Pitfalls of Deep Kernel Learningcited by 0
  20. 2025Contrastive Learning for Semi-Supervised Deep Regression with Generalized Ordinal Rankings from Spectral Seriationcited by 0
  21. 2026SpecRegMatch: Robust Semi-Supervised Regression for Vehicle Interior Noise Predictioncited by 0
  22. 2026CoGameReg: Cooperative-Game-Based Collaborative Semi-Supervised Regression for Seismic Reservoir Property Predictioncited by 0