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laplace approximation

70 papers

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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

Laplace Approximation Based Epistemic Uncertainty Estimation in 3D Object Detection CORL 2022
Laplacian Autoencoders for Learning Stochastic Representations NIPS 2022
Laplace approximated Gaussian process state-space models UAI 2022
Bayesian Deep Learning via Subnetwork Inference ICML 2021
Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors JMLR 2021
Differentially Private Regression and Classification with Sparse Gaussian Processes JMLR 2021
Laplace Redux - Effortless Bayesian Deep Learning NIPS 2021
Learnable uncertainty under Laplace approximations UAI 2021
Improving predictions of Bayesian neural nets via local linearization AISTATS 2021
Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning ICML 2021
Addressing Catastrophic Forgetting in Few-Shot Problems ICML 2021
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond NIPS 2020
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU Networks ICML 2020
Towards Zero-shot Language Modeling IJCNLP 2019
Towards Zero-shot Language Modeling EMNLP 2019
Dependent relevance determination for smooth and structured sparse regression JMLR 2019
LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations ICML 2019
Variational Laplace Autoencoders ICML 2019
Fast Automatic Smoothing for Generalized Additive Models JMLR 2019
State Space Gaussian Processes with Non-Gaussian Likelihood ICML 2018
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting NIPS 2018
Graphical model inference: Sequential Monte Carlo meets deterministic approximations NIPS 2018
Scalable Variational Inference for Super Resolution Microscopy AISTATS 2017
Fast Bayesian Intensity Estimation for the Permanental Process ICML 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference NIPS 2017