conftrace_

posterior sampling

152 papers

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PS

Co-occurring keywords

bayesian inference (1907) markov chain monte carlo (725) regret bound (1926) diffusion model (3751) langevin dynamics (128) inverse problem (240) generative model (2892) reinforcement learning (4352) thompson sampling (237) uncertainty quantification (1393)

Papers

Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusion CVPR 2024
Unsupervised Anomaly Detection via Masked Diffusion Posterior Sampling IJCAI 2024
pcaGAN: Improving Posterior-Sampling cGANs via Principal Component Regularization NIPS 2024
Deep Graph Neural Networks via Posteriori-Sampling-based Node-Adaptative Residual Module NIPS 2024
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo AISTATS 2024
Improving Diffusion-Based Image Restoration with Error Contraction and Error Correction AAAI 2024
Robust Approximate Sampling via Stochastic Gradient Barker Dynamics AISTATS 2024
Sequential Decision Making with Expert Demonstrations under Unobserved Heterogeneity NIPS 2024
Bayesian Semi-structured Subspace Inference AISTATS 2024
Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach WACV 2024
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors ICLR 2024
Learning Diffusion Priors from Observations by Expectation Maximization NIPS 2024
A Bayesian Approach to Data Point Selection NIPS 2024
Prior-dependent analysis of posterior sampling reinforcement learning with function approximation AISTATS 2024
Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstruction NIPS 2024
Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint AISTATS 2024
MDFL: Multi-Domain Diffusion-Driven Feature Learning AAAI 2024
Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors NIPS 2024
Double Randomized Underdamped Langevin with Dimension-Independent Convergence Guarantee NIPS 2023
Posterior Tracking Algorithm for Classification Bandits AISTATS 2023
Posterior sampling-based online learning for the stochastic shortest path model UAI 2023
Self-Correcting Bayesian Optimization through Bayesian Active Learning NIPS 2023
Posterior Sampling for Deep Reinforcement Learning ICML 2023
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent NIPS 2023
Conditional score-based diffusion models for Bayesian inference in infinite dimensions NIPS 2023