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Bayesian Inference

4821 directly classified papers

Papers per year

Papers

Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning ICML 2023
Exploration via Epistemic Value Estimation AAAI 2023
Fundamental limits and algorithms for sparse linear regression with sublinear sparsity JMLR 2023
Tree-AMP: Compositional Inference with Tree Approximate Message Passing JMLR 2023
On the geometry of Stein variational gradient descent JMLR 2023
Flow Matching for Scalable Simulation-Based Inference NIPS 2023
Bayesian Data Selection JMLR 2023
PFNs4BO: In-Context Learning for Bayesian Optimization ICML 2023
Planning with Hidden Parameter Polynomial MDPs AAAI 2023
Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models NIPS 2023
A Bayesian Approach To Analysing Training Data Attribution In Deep Learning NIPS 2023
Bayesian Spiked Laplacian Graphs JMLR 2023
Bayesian Cross-Modal Alignment Learning for Few-Shot Out-of-Distribution Generalization AAAI 2023
Hyperbolic VAE via Latent Gaussian Distributions NIPS 2023
Bayesian Optimization with Cost-varying Variable Subsets NIPS 2023
Probabilistic Shape Models of Anatomy Directly from Images AAAI 2023
Progressive Bayesian Inference for Scribble-Supervised Semantic Segmentation AAAI 2023
Online Restless Bandits with Unobserved States ICML 2023
VOCE: Variational Optimization with Conservative Estimation for Offline Safe Reinforcement Learning NIPS 2023
Discriminability and Transferability Estimation: A Bayesian Source Importance Estimation Approach for Multi-Source-Free Domain Adaptation AAAI 2023
Uncertainty Quantification via Neural Posterior Principal Components NIPS 2023
Learning Logical Reasoning Using an Intelligent Tutoring System: A Hybrid Approach to Student Modeling AAAI 2023
Variational Open-Domain Question Answering ICML 2023
Offline Meta Reinforcement Learning with In-Distribution Online Adaptation ICML 2023
Few-Shot Object Detection via Variational Feature Aggregation AAAI 2023