conftrace_

gaussian process

1200 papers

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Also known as

GP

Co-occurring keywords

variational inference (2069) bayesian optimization (624) bayesian inference (1907) uncertainty quantification (1393) kernel methods (1097) gaussian processes (89) regret bound (1926) active learning (1301) sparse approximation (76) hyperparameter optimization (406)

Papers

Transfer Learning with Gaussian Processes for Bayesian Optimization AISTATS 2022
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization AISTATS 2022
Monte Carlo Tree Descent for Black-Box Optimization NIPS 2022
Gaussian Process Bandits with Aggregated Feedback AAAI 2022
Efficient Approximate Inference for Stationary Kernel on Frequency Domain ICML 2022
Revisiting Active Sets for Gaussian Process Decoders NIPS 2022
Instance Dependent Regret Analysis of Kernelized Bandits ICML 2022
On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels NIPS 2022
Spectral Representation of Robustness Measures for Optimization Under Input Uncertainty ICML 2022
Bayesian federated estimation of causal effects from observational data UAI 2022
Fast and Scalable Spike and Slab Variable Selection in High-Dimensional Gaussian Processes AISTATS 2022
High-dimensional Additive Gaussian Processes under Monotonicity Constraints NIPS 2022
Supervising the Multi-Fidelity Race of Hyperparameter Configurations NIPS 2022
Sample-Then-Optimize Batch Neural Thompson Sampling NIPS 2022
Modelling Non-Smooth Signals with Complex Spectral Structure AISTATS 2022
Batch Bayesian optimisation via density-ratio estimation with guarantees NIPS 2022
AutoIP: A United Framework to Integrate Physics into Gaussian Processes ICML 2022
Gaussian Process Uniform Error Bounds with Unknown Hyperparameters for Safety-Critical Applications ICML 2022
Bayesian Optimization for Distributionally Robust Chance-constrained Problem ICML 2022
Byzantine-tolerant federated Gaussian process regression for streaming data NIPS 2022
Doubly Mixed-Effects Gaussian Process Regression AISTATS 2022
Adaptive Gaussian Process Change Point Detection ICML 2022
Symplectic Spectrum Gaussian Processes: Learning Hamiltonians from Noisy and Sparse Data NIPS 2022
Learning Fractional White Noises in Neural Stochastic Differential Equations NIPS 2022
Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes ICML 2022