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
Probabilistic circuits that know what they don’t know
UAI 2023
Protein Design with Guided Discrete Diffusion
NIPS 2023
Improving Diachronic Word Sense Induction with a Nonparametric Bayesian method
ACL 2023
Bayesian inference approach for entropy regularized reinforcement learning with stochastic dynamics
UAI 2023
Approximately Bayes-optimal pseudo-label selection
UAI 2023
Heteroskedastic Geospatial Tracking with Distributed Camera Networks
UAI 2023
Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning
UAI 2023
Posterior sampling-based online learning for the stochastic shortest path model
UAI 2023
Modeling Instance Interactions for Joint Information Extraction with Neural High-Order Conditional Random Field
ACL 2023
Non-adversarial training of Neural SDEs with signature kernel scores
NIPS 2023
Sample-efficient Multi-objective Molecular Optimization with GFlowNets
NIPS 2023
Establishing Markov equivalence in cyclic directed graphs
UAI 2023
Investigating a Generalization of Probabilistic Material Implication and Bayesian Conditionals
UAI 2023
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual Prostheses
NIPS 2023
Self-Correcting Bayesian Optimization through Bayesian Active Learning
NIPS 2023
Approximate inference of marginals using the IBIA framework
NIPS 2023
Robust Bayesian Satisficing
NIPS 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective
NIPS 2023
Provable convergence guarantees for black-box variational inference
NIPS 2023
A Bayesian Take on Gaussian Process Networks
NIPS 2023
Learning via Wasserstein-Based High Probability Generalisation Bounds
NIPS 2023
Query-Efficient Black-Box Red Teaming via Bayesian Optimization
ACL 2023
On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making
NIPS 2023
Generalization in the Face of Adaptivity: A Bayesian Perspective
NIPS 2023
PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning
NIPS 2023
<
1
…
46
47
48
…
193
>