stochastic variational inference

Accurate and Scalable Stochastic Gaussian Process Regression via Learnable Coreset-based Variational Inference UAI 2025 Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference UAI 2025 Idiographic Personality Gaussian Process for Psychological Assessment NeurIPS 2024 Robust and Scalable Gaussian Process Regression and Its Applications CVPR 2023 BayesAdapter: Being Bayesian, Inexpensively and Reliably, via Bayesian Fine-tuning ACML 2022 Deep Attentive Variational Inference ICLR 2022 Doubly Mixed-Effects Gaussian Process Regression AISTATS 2022 Generalised GPLVM with Stochastic Variational Inference AISTATS 2022 Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations AISTATS 2022 Input Dependent Sparse Gaussian Processes ICML 2022 A Differentiable Point Process with Its Application to Spiking Neural Networks ICML 2021 Automatic structured variational inference AISTATS 2021 Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features NeurIPS 2021 Conditioning Sparse Variational Gaussian Processes for Online Decision-making NeurIPS 2021 Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting AAAI 2021 Local Competition and Stochasticity for Adversarial Robustness in Deep Learning AISTATS 2021 Probabilistic selection of inducing points in sparse Gaussian processes UAI 2021 Tracking Disease Outbreaks from Sparse Data with Bayesian Inference AAAI 2021 Automated Augmented Conjugate Inference for Non-conjugate Gaussian Process Models AISTATS 2020 Improving model calibration with accuracy versus uncertainty optimization NeurIPS 2020 Scalable Gradients for Stochastic Differential Equations AISTATS 2020 Sparse Orthogonal Variational Inference for Gaussian Processes AISTATS 2020 Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes AAAI 2020 When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes NeurIPS 2020 Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019