mlsanityData to 7 Oct 2026

Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation

arXiv 1905.09670 ↗First posted 23 May 2019stat.ML cs.LGcited by 16

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Abstract (arXiv)

We propose a new scalable multi-class Gaussian process classification approach building on a novel modified softmax likelihood function. The new likelihood has two benefits: it leads to well-calibrated uncertainty estimates and allows for an efficient latent variable augmentation. The augmented model has the advantage that it is conditionally conjugate leading to a fast variational inference method via block coordinate ascent updates. Previous approaches suffered from a trade-off between uncertainty calibration and speed. Our experiments show that our method leads to well-calibrated uncertainty estimates and competitive predictive performance while being up to two orders faster than the state of the art.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 May 2019.

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Citing papers per year: 2021: 4; 2022: 4; 2023: 3; 2024: 2; 2025: 2; 2026: 1.

16 papers.

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  1. 2021Personalized Federated Learning with Gaussian Processescited by 76
  2. 2021GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learningcited by 26
  3. 2021Adaptive Inducing Points Selection For Gaussian Processescited by 8
  4. 2022Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervisioncited by 8
  5. 2022Transductive Decoupled Variational Inference for Few-Shot Classificationcited by 7
  6. 2021Scalable Cross Validation Losses for Gaussian Process Modelscited by 6
  7. 2022Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervisioncited by 6
  8. 2023Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classificationcited by 6
  9. 2023Heterogeneous Multi-Task Gaussian Cox Processescited by 4
  10. 2025Rethinking Approximate Gaussian Inference in Classificationcited by 2
  11. 2022Easy Variational Inference for Categorical Models via an Independent Binary Approximationcited by 1
  12. 2024Accelerating Convergence in Bayesian Few-Shot Classificationcited by 1
4 more
  1. 2024Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regressioncited by 1
  2. 2025Few-Shot Speech Deepfake Detection Adaptation with Gaussian Processescited by 1
  3. 2023On the Calibration and Uncertainty with P'olya-Gamma Augmentation for Dialog Retrieval Modelscited by 0
  4. 2026Simplex-to-Euclidean Bijection for Conjugate and Calibrated Multiclass Gaussian Process Classificationcited by 0