Posterior Inference

March 17, 2023

Posterior Estimation Using Deep Learning: A Simulation Study of Compartmental Modeling in Dynamic PET
Xiaofeng Liu, Thibault Marin, Tiss Amal, Jonghye Woo, Georges El Fakhri, Jinsong Ouyang
Deep Learning Simulation Study Posterior Inference Positron Emission Tomography Posterior Distribution Compartmental Model Conditional Variational Auto Encoder
Batch Updating of a Posterior Tree Distribution over a Meta-Tree
Yuta Nakahara, Toshiyasu Matsushima
Posterior Inference Meta Tree Batch Editing Posterior Tree Distribution Data Generation Model

February 6, 2023

Sampling-Based Accuracy Testing of Posterior Estimators for General Inference
Pablo Lemos, Adam Coogan, Yashar Hezaveh, Laurence Perreault-Levasseur
Posterior Inference Posterior Sampling Generative Factor Parameter Inference Accuracy Measurement

January 9, 2023

January 8, 2023

Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions
Marelys Crespo Navas, Sébastien Gadat, Xavier Gendre
Langevin Dynamic Posterior Inference Stochastic Way Langevin Monte Carlo Log Concave \Varepsilon$ Cover

December 20, 2022

Inversion of Bayesian Networks
Jesse van Oostrum, Peter van Hintum, Nihat Ay
Variational Autoencoders Bayesian Network Posterior Inference Probabilistic Graphical Model Eta Inversion

December 15, 2022

Bayesian posterior approximation with stochastic ensembles
Oleksandr Balabanov, Bernhard Mehlig, Hampus Linander
Variational Inference Deep Ensemble Posterior Inference Posterior Approximation Stochastic Neural Network Bayesian Ensemble

November 29, 2022

Posterior Sampling for Continuing Environments
Wanqiao Xu, Shi Dong, Benjamin Van Roy
Reinforcement Learning Posterior Inference Posterior Sampling Continuous Environment Bayesian Regret Agent Environment Interaction

October 27, 2022

ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images
Matthew D. Hoffman, Tuan Anh Le, Pavel Sountsov, Christopher Suter, Ben Lee, Vikash K. Mansinghka, Rif A. Saurous
Neural Radiance Field Variational Autoencoder 3D Object 3D Shape Posterior Inference Probabilistic Generative Model 2 Dimensional Image

October 26, 2022

Bayesian Hyperbolic Multidimensional Scaling
Bolun Liu, Shane Lubold, Adrian E. Raftery, Tyler H. McCormick
Posterior Inference Low Dimensional Manifold Multidimensional Scaling Hyperbolic Model Hyperbolic Scaling

October 11, 2022

Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference
Maximilian Dax, Stephen R. Green, Jonathan Gair, Michael Pürrer, Jonas Wildberger, Jakob H. Macke, Alessandra Buonanno, Bernhard Schölkopf
Scientific Inference Posterior Inference Importance Sampling Gravitational Wave Neural Posterior Estimation

September 15, 2022

On the detrimental effect of invariances in the likelihood for variational inference
Richard Kurle, Ralf Herbrich, Tim Januschowski, Yuyang Wang, Jan Gasthaus
Variational Inference Mean Field Posterior Inference Alpha Invariance

September 6, 2022

Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution
Joel Janek Dabrowski, Daniel Edward Pagendam
Variational Inference Bayesian Neural Network Posterior Inference Posterior Approximation Implicit Model Posterior Predictive Approximate Bayesian Inference Bayesian Neural

August 22, 2022

Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference
Wonyeol Lee, Xavier Rival, Hongseok Yang
Application Proficiency Variational Inference Posterior Inference Gradient Estimator Average Smoothness Probabilistic Program Differentiable Model

June 15, 2022

Federated Learning with Uncertainty via Distilled Predictive Distributions
Shrey Bhatt, Aishwarya Gupta, Piyush Rai
High Uncertainty Anticipation Posterior Inference Predictive Uncertainty Posterior Predictive Posterior Distribution Predictive Distribution

June 8, 2022

Benchmarking Bayesian neural networks and evaluation metrics for regression tasks
Brian Staber, Sébastien Da Veiga
Uncertainty Quantification Bayesian Neural Network Evaluation Metric Posterior Inference Regression Task Posterior Approximation Kernel Stein Discrepancy

June 1, 2022

Asymptotic Properties for Bayesian Neural Network in Besov Space
Kyeongwon Lee, Jaeyong Lee
Bayesian Neural Network Posterior Inference Prior Distribution Function Space

May 31, 2022

Simulator-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems
Luca Masserano, Tommaso Dorigo, Rafael Izbicki, Mikael Kuusela, Ann B. Lee
Scientific Inference Inverse Problem Posterior Inference Parameter Inference Predictive Algorithm Neural Density Confidence Region

May 20, 2022

Sparse Infinite Random Feature Latent Variable Modeling
Michael Minyi Zhang
Latent Variable Posterior Inference Latent Variable Model

Papers

Posterior Estimation Using Deep Learning: A Simulation Study of Compartmental Modeling in Dynamic PET

Batch Updating of a Posterior Tree Distribution over a Meta-Tree

Sampling-Based Accuracy Testing of Posterior Estimators for General Inference

Bayesian Additive Main Effects and Multiplicative Interaction Models using Tensor Regression for Multi-environmental Trials

Fast and Correct Gradient-Based Optimisation for Probabilistic Programming via Smoothing

Stochastic Langevin Monte Carlo for (weakly) log-concave posterior distributions

Inversion of Bayesian Networks

Bayesian posterior approximation with stochastic ensembles

Posterior Sampling for Continuing Environments

ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images

Bayesian Hyperbolic Multidimensional Scaling

Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference

On the detrimental effect of invariances in the likelihood for variational inference

Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution

Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference

Federated Learning with Uncertainty via Distilled Predictive Distributions

Benchmarking Bayesian neural networks and evaluation metrics for regression tasks

Asymptotic Properties for Bayesian Neural Network in Besov Space

Simulator-Based Inference with Waldo: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems

Sparse Infinite Random Feature Latent Variable Modeling