{"total":15,"rows":[{"id":"2106.01413","title":"Rectangular Flows for Manifold Learning","created":"2021-06-02","cited_by_count":50,"area":null},{"id":"2205.15449","title":"Posterior and Computational Uncertainty in Gaussian Processes","created":"2022-05-30","cited_by_count":24,"area":null},{"id":"2107.00243","title":"Preconditioning for Scalable Gaussian Process Hyperparameter Optimization","created":"2021-07-01","cited_by_count":23,"area":null},{"id":"2112.15246","title":"When are Iterative Gaussian Processes Reliably Accurate?","created":"2021-12-31","cited_by_count":12,"area":null},{"id":"2310.17137","title":"Large-Scale Gaussian Processes via Alternating Projection","created":"2023-10-26","cited_by_count":11,"area":null},{"id":"2106.06695","title":"SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes","created":"2021-06-12","cited_by_count":9,"area":null},{"id":"2411.01036","title":"Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference","created":"2024-11-01","cited_by_count":9,"area":null},{"id":"2202.01694","title":"Variational Nearest Neighbor Gaussian Process","created":"2022-02-03","cited_by_count":8,"area":null},{"id":"2206.11267","title":"Neural Implicit Manifold Learning for Topology-Aware Density Estimation","created":"2022-06-22","cited_by_count":5,"area":null},{"id":"2210.01534","title":"Multi-fidelity Monte Carlo: a pseudo-marginal approach","created":"2022-10-04","cited_by_count":4,"area":null},{"id":"2112.03638","title":"Scaling Structured Inference with Randomization","created":"2021-12-07","cited_by_count":2,"area":null},{"id":"2402.09849","title":"Recommendations for Baselines and Benchmarking Approximate Gaussian Processes","created":"2024-02-15","cited_by_count":2,"area":null},{"id":"2502.01861","title":"Learning Hyperparameters via a Data-Emphasized Variational Objective","created":"2025-02-03","cited_by_count":2,"area":null},{"id":"2109.09417","title":"Barely Biased Learning for Gaussian Process Regression","created":"2021-09-20","cited_by_count":0,"area":null},{"id":"2403.13300","title":"Kernel Multigrid: Accelerate Back-fitting via Sparse Gaussian Process Regression","created":"2024-03-20","cited_by_count":0,"area":null}],"next_cursor":null}