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Bayesian & Probabilistic

3,963 papers (2 classified directly here)

Subtopics

Probabilistic Modeling (2,252) Variational Inference (802) Gaussian Processes (570) Bayesian Learning (455) Bayesian Optimization (221) Markov Chain Monte Carlo (143) Nonparametric Bayesian (86) Bayesian Networks (81) Conditional Random Fields (5)

Papers per year

9
118
124
394
151
'05
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'25

Papers (including subtopics)

Improving Model Probability Calibration by Integration of Large Data Sources with Biased Labels AAAI 2025
Offline-to-Online Hyperparameter Transfer for Stochastic Bandits AAAI 2025
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood AAAI 2025
On the Relationship Between Monotone and Squared Probabilistic Circuits AAAI 2025
Probabilistic Forecasting of Irregularly Sampled Time Series with Missing Values via Conditional Normalizing Flows AAAI 2025
Conditional Diffusion Models Based Conditional Independence Testing AAAI 2025
Asynchronous Distributed Gaussian Process Regression AAAI 2025
Supervised Score-Based Modeling by Gradient Boosting AAAI 2025
Simulation-Free Hierarchical Latent Policy Planning for Proactive Dialogues AAAI 2025
Bayesian Optimization for Unknown Cost-Varying Variable Subsets with No-Regret Costs AAAI 2025
Trading Off Quality and Uncertainty Through Multi-Objective Optimisation in Batch Bayesian Optimisation AAAI 2025
Expensive Multi-Objective Bayesian Optimization Based on Diffusion Models AAAI 2025
Optimizing Heat Alert Issuance with Reinforcement Learning AAAI 2025
Realizing AI for Impact: Towards Participatory Human-AI Collaboration for Water Conservation and Reproductive Health AAAI 2025
De Novo Molecular and Crystal Design with Latent Space Bayesian Optimization AAAI 2025
Hypernetwork Approach to Bayesian MAML (Student Abstract) AAAI 2025
Drift: Enhancing LLM Faithfulness in Rationale Generation via Dual-Reward Probabilistic Inference ACL 2025
Extending Complex Logical Queries on Uncertain Knowledge Graphs ACL 2025
IRT-Router: Effective and Interpretable Multi-LLM Routing via Item Response Theory ACL 2025
Impartial Multi-task Representation Learning via Variance-invariant Probabilistic Decoding ACL 2025
Language Model Probabilities are Not Calibrated in Numeric Contexts ACL 2025
A Spatio-Temporal Point Process for Fine-Grained Modeling of Reading Behavior ACL 2025
A Variational Approach for Mitigating Entity Bias in Relation Extraction ACL 2025
Enhancing NER by Harnessing Multiple Datasets with Conditional Variational Autoencoders ACL 2025
Statistical inference on black-box generative models in the data kernel perspective space ACL 2025