conftrace_

laplace approximation

70 papers

Explore in graph

Also known as

LA

Co-occurring keywords

bayesian inference (1907) variational inference (2069) gaussian process (1200) markov chain monte carlo (725) expectation propagation (86) marginal likelihood (75) uncertainty quantification (1393) posterior approximation (132) bayesian neural network (201) approximate inference (253)

Papers

Diffusion Epistemic Uncertainty with Asymmetric Learning for Diffusion-Generated Image Detection ICCV 2025
Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection WACV 2025
How good is your Laplace approximation of the Bayesian posterior? Finite-sample computable error bounds for a variety of useful divergences JMLR 2025
FSP-Laplace: Function-Space Priors for the Laplace Approximation in Bayesian Deep Learning NIPS 2024
Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Models NIPS 2024
Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks using the Marginal Likelihood NIPS 2024
Solving Spectrum Unmixing as a Multi-Task Bayesian Inverse Problem with Latent Factors for Endmember Variability AAAI 2024
Low-rank Variational Bayes correction to the Laplace method JMLR 2024
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation NIPS 2024
Reparameterization invariance in approximate Bayesian inference NIPS 2024
Online Posterior Sampling with a Diffusion Prior NIPS 2024
Riemannian Laplace Approximation with the Fisher Metric AISTATS 2024
Sparse Spectral Bayesian Permanental Process with Generalized Kernel AISTATS 2023
Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval NIPS 2023
Diversity-enhanced probabilistic ensemble for uncertainty estimation UAI 2023
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels ICML 2023
The Fine Print on Tempered Posteriors ACML 2023
GEX: A flexible method for approximating influence via Geometric Ensemble NIPS 2023
Effective Bayesian Heteroscedastic Regression with Deep Neural Networks NIPS 2023
Bayesian numerical integration with neural networks UAI 2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models ICML 2023
Riemannian Laplace approximations for Bayesian neural networks NIPS 2023
Learning Layer-wise Equivariances Automatically using Gradients NIPS 2023
Laplace Approximation Based Epistemic Uncertainty Estimation in 3D Object Detection CORL 2022
Laplace approximated Gaussian process state-space models UAI 2022