Lin, Jihao Andreas

7 publications

ICML 2025 Scalable Gaussian Processes with Latent Kronecker Structure Jihao Andreas Lin, Sebastian Ament, Maximilian Balandat, David Eriksson, José Miguel Hernández-Lobato, Eytan Bakshy

NeurIPS 2024 Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes Jihao Andreas Lin, Shreyas Padhy, Bruno Mlodozeniec, Javier Antorán, José Miguel Hernández-Lobato

NeurIPSW 2024 Scaling Gaussian Processes for Learning Curve Prediction via Latent Kronecker Structure Jihao Andreas Lin, Sebastian Ament, Maximilian Balandat, Eytan Bakshy

ICLR 2024 Stochastic Gradient Descent for Gaussian Processes Done Right Jihao Andreas Lin, Shreyas Padhy, Javier Antoran, Austin Tripp, Alexander Terenin, Csaba Szepesvari, José Miguel Hernández-Lobato, David Janz

ICMLW 2023 Beyond Intuition, a Framework for Applying GPs to Real-World Data Kenza Tazi, Jihao Andreas Lin, Ross Viljoen, Alex Gardner, S. T. John, Hong Ge, Richard E Turner

ICMLW 2023 Minimal Random Code Learning with Mean-KL Parameterization Jihao Andreas Lin, Gergely Flamich, José Miguel Hernández-Lobato

NeurIPS 2023 Sampling from Gaussian Process Posteriors Using Stochastic Gradient Descent Jihao Andreas Lin, Javier Antorán, Shreyas Padhy, David Janz, José Miguel Hernández-Lobato, Alexander Terenin