laplace approximation

LazyDINO: Fast, Scalable, and Efficiently Amortized Bayesian Inversion via Structure-Exploiting and Surrogate-Driven Measure Transport JMLR 2026 Vecchia-Inducing-Points Full-Scale Approximations for Gaussian Processes JMLR 2026 Debiasing Mini-Batch Quadratics for Applications in Deep Learning ICLR 2025 Diffusion Epistemic Uncertainty with Asymmetric Learning for Diffusion-Generated Image Detection ICCV 2025 Do Bayesian Neural Networks Actually Behave Like Bayesian Models? ICML 2025 FedBEns: One-Shot Federated Learning based on Bayesian Ensemble ICML 2025 Generative Uncertainty in Diffusion Models UAI 2025 How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences JMLR 2025 Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection WACV 2025 Variation Due to Regularization Tractably Recovers Bayesian Deep Learning Uncertainty AISTATS 2025 BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference ICLR 2024 Bayesian Low-rank Adaptation for Large Language Models ICLR 2024 Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data ICLR 2024 FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NeurIPS 2024 FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning NeurIPS 2024 Low-rank Variational Bayes correction to the Laplace method JMLR 2024 Online Posterior Sampling with a Diffusion Prior NeurIPS 2024 Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models NeurIPS 2024 Reparameterization invariance in approximate Bayesian inference NeurIPS 2024 Riemannian Laplace Approximation with the Fisher Metric AISTATS 2024 Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood NeurIPS 2024 Solving Spectrum Unmixing as a Multi-Task Bayesian Inverse Problem with Latent Factors for Endmember Variability AAAI 2024 Towards Scalable Bayesian Transformers: Investigating stochastic subset selection for NLP UAI 2024 Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval NeurIPS 2023 Bayesian numerical integration with neural networks UAI 2023