gaussian process

Towards Scalable Coverage-Based Testing of Autonomous Vehicles CoRL 2023 Tractable and Near-Optimal Adversarial Algorithms for Robust Estimation in Contaminated Gaussian Models JMLR 2023 Training-Free Neural Active Learning with Initialization-Robustness Guarantees ICML 2023 Transfer NAS with Meta-learned Bayesian Surrogates ICLR 2023 Transformed Gaussian Processes for Characterizing a Model’s Discrepancy ACML 2023 Uncertainty Estimation for Molecules: Desiderata and Methods ICML 2023 Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles ICLR 2023 Unsupervised representation learning with recognition-parametrised probabilistic models AISTATS 2023 Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction CVPR 2023 Variational Gaussian processes for linear inverse problems NeurIPS 2023 Variational Gaussian Processes with Decoupled Conditionals NeurIPS 2023 Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models NeurIPS 2023 Wide stochastic networks: Gaussian limit and PAC-Bayesian training ALT 2023 Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders ICML 2022 Accurate and Scalable Gaussian Processes for Fine-Grained Air Quality Inference AAAI 2022 Active Bayesian Causal Inference NeurIPS 2022 Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization AISTATS 2022 Adaptive Gaussian Process Change Point Detection ICML 2022 Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets AISTATS 2022 Additive Gaussian Processes Revisited ICML 2022 Adjoint-aided inference of Gaussian process driven differential equations NeurIPS 2022 Adversarial Attacks on Gaussian Process Bandits ICML 2022 Adversarial Robustness Guarantees for Gaussian Processes JMLR 2022 A generalization of the randomized singular value decomposition ICLR 2022 AK: Attentive Kernel for Information Gathering RSS 2022