gaussian process

Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input NeurIPS 2024 MetaMetrics-MT: Tuning Meta-Metrics for Machine Translation via Human Preference Calibration EMNLP 2024 Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes ICLR 2024 Minimizing UCB: a Better Local Search Strategy in Local Bayesian Optimization NeurIPS 2024 Model-Based Transfer Learning for Contextual Reinforcement Learning NeurIPS 2024 Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems NeurIPS 2024 Multi-Agent Learning in Contextual Games under Unknown Constraints AISTATS 2024 Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity UAI 2024 Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data ICLR 2024 Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions ICML 2024 NeoRL: Efficient Exploration for Nonepisodic RL NeurIPS 2024 Noise-Aware Differentially Private Regression via Meta-Learning NeurIPS 2024 Nonstationary Sparse Spectral Permanental Process NeurIPS 2024 No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints AISTATS 2024 No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes UAI 2024 Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees JMLR 2024 On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory NeurIPS 2024 PG-LBO: Enhancing High-Dimensional Bayesian Optimization with Pseudo-Label and Gaussian Process Guidance AAAI 2024 Physically consistent modeling & identification of nonlinear friction with dissipative Gaussian processes L4DC 2024 Physics-constrained learning of PDE systems with uncertainty quantified port-Hamiltonian models L4DC 2024 Physics-Informed Variational State-Space Gaussian Processes NeurIPS 2024 POAM: Probabilistic Online Attentive Mapping for Efficient Robotic Information Gathering RSS 2024 Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance UAI 2024 Prediction Error-based Classification for Class-Incremental Learning ICLR 2024 Pre-trained Gaussian Processes for Bayesian Optimization JMLR 2024