gaussian process

Information theoretic meta learning with Gaussian processes UAI 2021 Interpretable Neural Architecture Search via Bayesian Optimisation with Weisfeiler-Lehman Kernels ICLR 2021 Isometric Gaussian Process Latent Variable Model for Dissimilarity Data ICML 2021 Kernel Functional Optimisation NeurIPS 2021 Kernel Identification Through Transformers NeurIPS 2021 Kernel Interpolation for Scalable Online Gaussian Processes AISTATS 2021 Large-width functional asymptotics for deep Gaussian neural networks ICLR 2021 Latent Gaussian process with composite likelihoods and numerical quadrature AISTATS 2021 Latent variable modeling with random features AISTATS 2021 Learning Compositional Sparse Gaussian Processes with a Shrinkage Prior AAAI 2021 Learning Deep Classifiers Consistent With Fine-Grained Novelty Detection CVPR 2021 Learning Nonparametric Volterra Kernels with Gaussian Processes NeurIPS 2021 Learning to Learn Dense Gaussian Processes for Few-Shot Learning NeurIPS 2021 Learning to learn with Gaussian processes UAI 2021 Lenient Regret and Good-Action Identification in Gaussian Process Bandits ICML 2021 Leveraging probabilistic circuits for nonparametric multi-output regression UAI 2021 Linearly Constrained Gaussian Processes with Boundary Conditions AISTATS 2021 Local Differential Privacy for Bayesian Optimization AAAI 2021 Location Trace Privacy Under Conditional Priors AISTATS 2021 Longitudinal Deep Kernel Gaussian Process Regression AAAI 2021 Longitudinal Variational Autoencoder AISTATS 2021 Marginalised Gaussian Processes with Nested Sampling NeurIPS 2021 Matérn Gaussian Processes on Graphs AISTATS 2021 Mean-Variance Analysis in Bayesian Optimization under Uncertainty AISTATS 2021 Misspecified Gaussian Process Bandit Optimization NeurIPS 2021