The Prediction of Reverberation Signals Based on Dynamic Models. - Xinmin Ren; Ning Wang; Yuling Yao (ICIC (3), 2007)

Yes, but Did It Work?: Evaluating Variational Inference. - Yuling Yao; Aki Vehtari; Daniel Simpson; Andrew Gelman (ICML, 2018)

Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network. - Oscar Chang; Yuling Yao; David Williams-King; Hod Lipson (CoRR, 2019)

Bayesian hierarchical stacking. - Yuling Yao; Gregor Pirs; Aki Vehtari; Andrew Gelman (CoRR, 2021)

Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors. - Yuling Yao; Aki Vehtari; Andrew Gelman (J. Mach. Learn. Res., 2022)

Variational Inference with Gaussian Score Matching. - Chirag Modi 002; Robert M. Gower; Charles Margossian; Yuling Yao; David M. Blei; Lawrence K. Saul (NeurIPS, 2023)

Discriminative Calibration: Check Bayesian Computation from Simulations and Flexible Classifier. - Yuling Yao; Justin Domke (NeurIPS, 2023)

Locking and Quacking: Stacking Bayesian model predictions by log-pooling and superposition. - Yuling Yao; Luiz Max Carvalho; Diego Mesquita; Yann McLatchie (CoRR, 2023)

Discriminative calibration. - Yuling Yao; Justin Domke (CoRR, 2023)

Simulation-Based Stacking. - Yuling Yao; Bruno Régaldo-Saint Blancard; Justin Domke (AISTATS, 2024)

Predictive variational inference: Learn the predictively optimal posterior distribution. - Jinlin Lai; Yuling Yao (CoRR, 2024)

Pareto Smoothed Importance Sampling. - Aki Vehtari; Daniel Simpson; Andrew Gelman; Yuling Yao; Jonah Gabry (J. Mach. Learn. Res., 2024)