Bayesian & Probabilistic
5,407 papers (3 classified directly here)
Subtopics · a paper can sit in several, so these overlap
Papers per year
1
2
5
7
4
9
71
90
96
90
127
113
152
198
196
168
213
197
273
389
460
470
455
481
482
385
273
2000
'5
'10
'15
'20
'25
Papers (including subtopics)
Probabilistic Symmetry for Multi-Agent Dynamics
L4DC 2023
Probabilistic Transformer: A Probabilistic Dependency Model for Contextual Word Representation
ACL 2023
Probabilistic Triangulation for Uncalibrated Multi-View 3D Human Pose Estimation
ICCV 2023
Probabilistic Volumetric Fusion for Dense Monocular SLAM
WACV 2023
Probabilities of Causation: Role of Observational Data
AISTATS 2023
Probably Approximate Shapley Fairness with Applications in Machine Learning
AAAI 2023
ProbVLM: Probabilistic Adapter for Frozen Vison-Language Models
ICCV 2023
Proper Scoring Rules for Survival Analysis
ICML 2023
Prototype-based Aleatoric Uncertainty Quantification for Cross-modal Retrieval
NeurIPS 2023
Provable convergence guarantees for black-box variational inference
NeurIPS 2023
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation
NeurIPS 2023
qEUBO: A Decision-Theoretic Acquisition Function for Preferential Bayesian Optimization
AISTATS 2023
Quantitative Universal Approximation Bounds for Deep Belief Networks
ICML 2023
Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates
UAI 2023
Reanalyzing L2 Preposition Learning with Bayesian Mixed Effects and a Pretrained Language Model
ACL 2023
Recovering Top-Two Answers and Confusion Probability in Multi-Choice Crowdsourcing
ICML 2023
Recurrent Neural Networks and Universal Approximation of Bayesian Filters
AISTATS 2023
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group
AISTATS 2023
Reinforcement Causal Structure Learning on Order Graph
AAAI 2023
Reliable and Interpretable Personalized Federated Learning
CVPR 2023
Resolving the Mixing Time of the Langevin Algorithm to its Stationary Distribution for Log-Concave Sampling
COLT 2023
Retrospective Uncertainties for Deep Models using Vine Copulas
AISTATS 2023
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification
NeurIPS 2023
Revisiting Structured Variational Autoencoders
ICML 2023
Rhino: Deep Causal Temporal Relationship Learning with History-dependent Noise
ICLR 2023