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← Optimization & Theory
Machine Learning
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Optimization & Theory
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Bayesian Inference
4,821 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
Fusing the Old with the New: Learning Relative Camera Pose with Geometry-Guided Uncertainty
CVPR 2021
Bayesian Inference for Optimal Transport with Stochastic Cost
ACML 2021
Bayesian Quadrature on Riemannian Data Manifolds
ICML 2021
Bayesian Adaptation for Covariate Shift
NIPS 2021
BayesIMP: Uncertainty Quantification for Causal Data Fusion
NIPS 2021
SDF-Bayes: Cautious Optimism in Safe Dose-Finding Clinical Trials with Drug Combinations and Heterogeneous Patient Groups
AISTATS 2021
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation
ICML 2021
Principled Exploration via Optimistic Bootstrapping and Backward Induction
ICML 2021
BayLIME: Bayesian local interpretable model-agnostic explanations
UAI 2021
On the difficulty of unbiased alpha divergence minimization
ICML 2021
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning
NIPS 2021
A sampling-based circuit for optimal decision making
NIPS 2021
VaB-AL: Incorporating Class Imbalance and Difficulty With Variational Bayes for Active Learning
CVPR 2021
Geometric rates of convergence for kernel-based sampling algorithms
UAI 2021
Enriching ImageNet With Human Similarity Judgments and Psychological Embeddings
CVPR 2021
Bayesian Inference with Certifiable Adversarial Robustness
AISTATS 2021
Practical and Rigorous Uncertainty Bounds for Gaussian Process Regression
AAAI 2021
Deep kernel processes
ICML 2021
Bias-Robust Bayesian Optimization via Dueling Bandits
ICML 2021
Recursive Bayesian Networks: Generalising and Unifying Probabilistic Context-Free Grammars and Dynamic Bayesian Networks
NIPS 2021
Fast Algorithms for Relational Marginal Polytopes
IJCAI 2021
Offline Meta Reinforcement Learning -- Identifiability Challenges and Effective Data Collection Strategies
NIPS 2021
Outcome-Driven Reinforcement Learning via Variational Inference
NIPS 2021
A variational approximate posterior for the deep Wishart process
NIPS 2021
A General Class of Transfer Learning Regression without Implementation Cost
AAAI 2021
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