sparse gaussian process

Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference UAI 2025 Secure Distributed Sparse Gaussian Process Models Using Multi-Key Homomorphic Encryption AAAI 2024 Sparse Variational Student-t Processes AAAI 2024 Calibrating Transformers via Sparse Gaussian Processes ICLR 2023 Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes ICML 2023 Inducing Point Allocation for Sparse Gaussian Processes in High-Throughput Bayesian Optimisation AISTATS 2023 Function-space Inference with Sparse Implicit Processes ICML 2022 Memory safe computations with XLA compiler NeurIPS 2022 Sparse Additive Gaussian Process Regression JMLR 2022 Deep Neural Networks as Point Estimates for Deep Gaussian Processes NeurIPS 2021 Direct Loss Minimization for Sparse Gaussian Processes AISTATS 2021 Probabilistic selection of inducing points in sparse Gaussian processes UAI 2021 Sparse within Sparse Gaussian Processes using Neighbor Information ICML 2021 Trust Your Robots! Predictive Uncertainty Estimation of Neural Networks with Sparse Gaussian Processes CoRL 2021 Scalable Variational Bayesian Kernel Selection for Sparse Gaussian Process Regression AAAI 2020 Deep Gaussian Processes with Importance-Weighted Variational Inference ICML 2019 Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks ICML 2019 Scalable Generalized Dynamic Topic Models AISTATS 2018 A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 Distributed Submodular Maximization JMLR 2016 Incremental Variational Sparse Gaussian Process Regression NeurIPS 2016 A Unifying Framework of Anytime Sparse Gaussian Process Regression Models with Stochastic Variational Inference for Big Data ICML 2015 Batch Continuous-Time Trajectory Estimation as Exactly Sparse Gaussian Process Regression RSS 2014 Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models NeurIPS 2014