mlsanityData to 7 Oct 2026

The Gaussian Neural Process

arXiv 2101.03606 ↗First posted 10 Jan 2021stat.ML cs.LGcited by 34

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Abstract (arXiv)

Neural Processes (NPs; Garnelo et al., 2018a,b) are a rich class of models for meta-learning that map data sets directly to predictive stochastic processes. We provide a rigorous analysis of the standard maximum-likelihood objective used to train conditional NPs. Moreover, we propose a new member to the Neural Process family called the Gaussian Neural Process (GNP), which models predictive correlations, incorporates translation equivariance, provides universal approximation guarantees, and demonstrates encouraging performance.

Key facts. Cited by 34 papers in the map (data through 7 Oct 2026). Builds on 12 of its 23 references that are in the map. First posted on arXiv 10 Jan 2021.

Builds on

12 of 23 references.

References · 12

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2016Matching Networks for One Shot Learningcited by 2,246
  3. 2018Conditional Neural Processescited by 421
  4. 2018Neural Processescited by 307
  5. 2019Attentive Neural Processescited by 280
  6. 2019Convolutional Conditional Neural Processescited by 139
  7. 2018Universal approximations of invariant maps by neural networkscited by 127
  8. 2019Functional Variational Bayesian Neural Networkscited by 127
  9. 2020Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processescited by 74
  10. 2015On Sparse variational methods and the Kullback-Leibler divergence between stochastic processescited by 56
  11. 2018Variational Implicit Processescited by 41
  12. 2019Scalable Training of Inference Networks for Gaussian-Process Modelscited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 10; 2023: 7; 2024: 3; 2025: 5; 2026: 6.

34 papers.

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  1. 2022Transformer Neural Processes: Uncertainty-Aware Meta Learning Via Sequence Modelingcited by 126
  2. 2021Priors in Bayesian Deep Learning: A Reviewcited by 101
  3. 2023Score-based Diffusion Models in Function Spacecited by 80
  4. 2022Neural Diffusion Processescited by 50
  5. 2023Autoregressive Conditional Neural Processescited by 32
  6. 2022Latent Bottlenecked Attentive Neural Processescited by 26
  7. 2022NP-Match: When Neural Processes meet Semi-Supervised Learningcited by 25
  8. 2021How Tight Can PAC-Bayes be in the Small Data Regime?cited by 24
  9. 2022The Neural Process Family: Survey, Applications and Perspectivescited by 23
  10. 2022Environmental Sensor Placement with Convolutional Gaussian Neural Processescited by 14
  11. 2023Practical Equivariances via Relational Conditional Neural Processescited by 13
  12. 2024Translation Equivariant Transformer Neural Processescited by 12
22 more
  1. 2022Evidential Conditional Neural Processescited by 10
  2. 2021Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Featurescited by 8
  3. 2025ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisitioncited by 8
  4. 2023Deep Stochastic Processes via Functional Markov Transition Operatorscited by 7
  5. 2025Flow Matching Neural Processescited by 6
  6. 2023NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic Segmentationcited by 5
  7. 2022Convolutional Neural Processes for Inpainting Satellite Imagescited by 4
  8. 2024Spectral Convolutional Conditional Neural Processescited by 4
  9. 2024Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Datacited by 4
  10. 2025Efficient Autoregressive Inference for Transformer Probabilistic Modelscited by 4
  11. 2023Adaptive Conditional Quantile Neural Processescited by 3
  12. 2022Incorporating Prior Knowledge into Neural Networks through an Implicit Composite Kernelcited by 2
  13. 2022Bayesian Convolutional Deep Sets with Task-Dependent Stationary Priorcited by 2
  14. 2025Sparse Gaussian Neural Processescited by 2
  15. 2026LLM Flow Processes for Text-Conditioned Regressioncited by 1
  16. 2023Function-Space Regularization for Deep Bayesian Classificationcited by 0
  17. 2025Neural Bridge Processescited by 0
  18. 2026Generative Neural Operators through Diffusion Last Layercited by 0
  19. 2026Spectral Transformer Neural Processescited by 0
  20. 2026Gaussian Mixture Copula Processes for Irregular Time Seriescited by 0
  21. 2026Revisiting Neural Processes via Fourier Transform and Volterra Seriescited by 0
  22. 2026Multi-Task Bayesian In-Context Learningcited by 0