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Bayesian & Probabilistic

4,335 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,599) Bayesian Learning (1,663) Bayesian Inference (523) Variational Inference (107) Gaussian Processes (6) Bayesian Networks (5)

Papers per year

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Papers (including subtopics)

Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification MIDL 2023
Neural Diffusion Processes ICML 2023
Adversarial Bayesian Augmentation for Single-Source Domain Generalization ICCV 2023
Evidential Conditional Neural Processes AAAI 2023
Provable convergence guarantees for black-box variational inference NIPS 2023
Exploring and Exploiting Uncertainty for Incomplete Multi-View Classification CVPR 2023
Gradient-Based Uncertainty Attribution for Explainable Bayesian Deep Learning CVPR 2023
Learning-augmented count-min sketches via Bayesian nonparametrics JMLR 2023
Variational Gaussian processes for linear inverse problems NIPS 2023
Probabilistic Imputation for Time-series Classification with Missing Data ICML 2023
Expressive probabilistic sampling in recurrent neural networks NIPS 2023
Not all Strongly Rayleigh Distributions Have Small Probabilistic Generating Circuits ICML 2023
Gradient-Free Kernel Stein Discrepancy NIPS 2023
Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision AISTATS 2023
Complexity of Probabilistic Inference in Random Dichotomous Hedonic Games AAAI 2023
A Bayesian Bradley-Terry model to compare multiple ML algorithms on multiple data sets JMLR 2023
Compression with Bayesian Implicit Neural Representations NIPS 2023
Diffusion-Based Probabilistic Uncertainty Estimation for Active Domain Adaptation NIPS 2023
Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023
The Unreasonable Effectiveness of Deep Evidential Regression AAAI 2023
Probabilistic Precision and Recall Towards Reliable Evaluation of Generative Models ICCV 2023
A Probabilistic Framework for Discovering New Intents ACL 2023
Flat Seeking Bayesian Neural Networks NIPS 2023
Leveraging Locality and Robustness to Achieve Massively Scalable Gaussian Process Regression NIPS 2023
Mixed-Effect Thompson Sampling AISTATS 2023