gaussian process

The Multiple Instance Learning Gaussian Process Probit Model AISTATS 2021 The promises and pitfalls of deep kernel learning UAI 2021 The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks JMLR 2021 Tracking Disease Outbreaks from Sparse Data with Bayesian Inference AAAI 2021 Tractable Approximate Gaussian Inference for Bayesian Neural Networks JMLR 2021 Trusted-maximizers entropy search for efficient Bayesian optimization UAI 2021 Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL NeurIPS 2021 Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric L4DC 2021 Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models MLHC 2021 Uncertainty quantification using martingales for misspecified Gaussian processes ALT 2021 Using Physics Knowledge for Learning Rigid-body Forward Dynamics with Gaussian Process Force Priors CoRL 2021 Value-at-Risk Optimization with Gaussian Processes ICML 2021 Variational Auto-Regressive Gaussian Processes for Continual Learning ICML 2021 Variational Inference for Continuous-Time Switching Dynamical Systems NeurIPS 2021 Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels NeurIPS 2021 Accelerated Bayesian Optimisation through Weight-Prior Tuning AISTATS 2020 Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization AISTATS 2020 A Finite-Sample Deviation Bound for Stable Autoregressive Processes L4DC 2020 All your loss are belong to Bayes NeurIPS 2020 An Interpretable and Sample Efficient Deep Kernel for Gaussian Process UAI 2020 Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models AISTATS 2020 Bandit optimisation of functions in the Matérn kernel RKHS AISTATS 2020 Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation UAI 2020 Bayesian Deep Ensembles via the Neural Tangent Kernel NeurIPS 2020 Bayesian Deep Learning and a Probabilistic Perspective of Generalization NeurIPS 2020