Research Explorer
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Papers
Trends
Conferences
Explore
Authors
Topics
Keywords
Achievements
About
Methodology
← Optimization & Theory
Machine Learning
›
Optimization & Theory
›
Bayesian Inference
4821 directly classified papers
Papers per year
2001: 1
2002: 1
2003: 5
2004: 2
2005: 9
2006: 22
2007: 32
2008: 36
2009: 38
2010: 72
2011: 86
2012: 85
2013: 148
2014: 179
2015: 162
2016: 183
2017: 255
2018: 278
2019: 458
2020: 469
2021: 554
2022: 477
2023: 576
2024: 348
2025: 255
2026: 90
Papers
Calibrating Neural Simulation-Based Inference with Differentiable Coverage Probability
NIPS 2023
Sampling from Structured Log-Concave Distributions via a Soft-Threshold Dikin Walk
NIPS 2023
Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation
NIPS 2023
A Kernel Stein Test of Goodness of Fit for Sequential Models
ICML 2023
Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation
JMLR 2023
Rehearsal Learning for Avoiding Undesired Future
NIPS 2023
Variational Inference for Deblending Crowded Starfields
JMLR 2023
Utilising the CLT Structure in Stochastic Gradient based Sampling : Improved Analysis and Faster Algorithms
COLT 2023
Uniqueness of BP fixed point for the Potts model and applications to community detection
COLT 2023
Wide stochastic networks: Gaussian limit and PAC-Bayesian training
ALT 2023
Energy Guided Diffusion for Generating Neurally Exciting Images
NIPS 2023
Estimating Noise Correlations Across Continuous Conditions With Wishart Processes
NIPS 2023
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
NIPS 2023
Fisher information lower bounds for sampling
ALT 2023
Task-Aware Risk Estimation of Perception Failures for Autonomous Vehicles
RSS 2023
Instance-Dependent Noisy Label Learning via Graphical Modelling
WACV 2023
Calibrating Uncertainty for Semi-Supervised Crowd Counting
ICCV 2023
The Memory-Perturbation Equation: Understanding Model's Sensitivity to Data
NIPS 2023
Adaptive Reordering Sampler with Neurally Guided MAGSAC
ICCV 2023
Learning Interpretable BEV Based VIO without Deep Neural Networks
CORL 2022
Interpretable Self-Aware Neural Networks for Robust Trajectory Prediction
CORL 2022
Data augmentation in Bayesian neural networks and the cold posterior effect
UAI 2022
Discriminator-Guided Model-Based Offline Imitation Learning
CORL 2022
Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments
CORL 2022
Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev
COLT 2022
<
1
…
50
51
52
…
193
>