Bayesian Optimization

Multi-Fidelity Bayesian Optimization via Deep Neural Networks NeurIPS 2020 ODIN: ODE-Informed Regression for Parameter and State Inference in Time-Continuous Dynamical Systems AAAI 2020 Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization AAAI 2020 Bayesian Functional Optimisation with Shape Prior AAAI 2019 Bayesian Optimization Meets Riemannian Manifolds in Robot Learning CoRL 2019 Bayesian Optimization under Heavy-tailed Payoffs NeurIPS 2019 Early-Stopping of Scattering Pattern Observation with Bayesian Modeling AAAI 2019 Efficient Neutrino Oscillation Parameter Inference with Gaussian Process AAAI 2019 MFBO-SSM: Multi-Fidelity Bayesian Optimization for Fast Inference in State-Space Models AAAI 2019 Multi-objective Bayesian optimisation with preferences over objectives NeurIPS 2019 Practical Two-Step Lookahead Bayesian Optimization NeurIPS 2019 Scalable Global Optimization via Local Bayesian Optimization NeurIPS 2019 Optimistic optimization of a Brownian NeurIPS 2018 Deep Kernels for Optimizing Locomotion Controllers CoRL 2017 Efficient Automatic Perception System Parameter Tuning On Site without Expert Supervision CoRL 2017 High Dimensional Bayesian Optimization using Dropout IJCAI 2017 Improving the Expected Improvement Algorithm NeurIPS 2017 Lookahead Bayesian Optimization with Inequality Constraints NeurIPS 2017 Multi-Information Source Optimization NeurIPS 2017 Bayesian optimization under mixed constraints with a slack-variable augmented Lagrangian NeurIPS 2016 Predictive Entropy Search for Multi-objective Bayesian Optimization ICML 2016 The Parallel Knowledge Gradient Method for Batch Bayesian Optimization NeurIPS 2016 Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NeurIPS 2016 Bayesian Optimization with Exponential Convergence NeurIPS 2015 Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions NeurIPS 2015