gaussian process

Learning of Sub-optimal Gait Controllers for Magnetic Walking Soft Millirobots RSS 2020 Learning Polynomials in Few Relevant Dimensions COLT 2020 Learning spectrograms with convolutional spectral kernels AISTATS 2020 Learning supported Model Predictive Control for Tracking of Periodic References L4DC 2020 Localized active learning of Gaussian process state space models L4DC 2020 Localizing and Amortizing: Efficient Inference for Gaussian Processes ACML 2020 Manifold GPLVMs for discovering non-Euclidean latent structure in neural data NeurIPS 2020 Matérn Gaussian Processes on Riemannian Manifolds NeurIPS 2020 Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization ICLR 2020 Mixed Strategies for Robust Optimization of Unknown Objectives AISTATS 2020 Modulating Surrogates for Bayesian Optimization ICML 2020 Monotonic Gaussian Process Flows AISTATS 2020 Multi-Fidelity Bayesian Optimization via Deep Neural Networks NeurIPS 2020 Multiplicative Gaussian Particle Filter AISTATS 2020 Multi-task Causal Learning with Gaussian Processes NeurIPS 2020 Near-linear time Gaussian process optimization with adaptive batching and resparsification ICML 2020 Noisy-Input Entropy Search for Efficient Robust Bayesian Optimization AISTATS 2020 Non-Parametric Calibration for Classification AISTATS 2020 Non-reversible Gaussian processes for identifying latent dynamical structure in neural data NeurIPS 2020 Non-separable Non-stationary random fields ICML 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems AAAI 2020 On Infinite-Width Hypernetworks NeurIPS 2020 On Simulation and Trajectory Prediction with Gaussian Process Dynamics L4DC 2020 Parametric Gaussian Process Regressors ICML 2020 Planning from Images with Deep Latent Gaussian Process Dynamics L4DC 2020