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bayesian learning

185 papers

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bayesian inference (1904) variational inference (2069) uncertainty quantification (1365) markov chain monte carlo (724) probabilistic modeling (851) posterior distribution (259) gaussian process (1198) transfer learning (5442) reinforcement learning (4122) stochastic gradient (296)

Papers

AI-Salesman: Towards Reliable Large Language Model Driven Telemarketing AAAI 2026
Differentiable Semantic Meta-Learning Framework for Long-Tail Motion Forecasting in Autonomous Driving AAAI 2026
On Evaluating LLMs’ Capabilities as Functional Approximators: A Bayesian Evaluation Framework COLING 2025
Context in Public Health for Underserved Communities: A Bayesian Approach to Online Restless Bandits AAAI 2025
EyeSeg: An Uncertainty-Aware Eye Segmentation Framework for AR/VR IJCAI 2025
Hypernetwork Approach to Bayesian MAML (Student Abstract) AAAI 2025
Replication-proof Bandit Mechanism Design with Bayesian Agents AAAI 2025
Cache-Efficient Posterior Sampling for Reinforcement Learning with LLM-Derived Priors Across Discrete and Continuous Domains EMNLP 2025
Multi-Attribute Multi-Grained Adaptation of Pre-Trained Language Models for Text Understanding from Bayesian Perspective AAAI 2025
A Bayesian account of pronoun and neopronoun acquisition NAACL 2025
Cross-Framework Generalizable Discourse Relation Classification Through Cognitive Dimensions NAACL 2025
Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the compact case JMLR 2024
Learning Sparse Codes with Entropy-Based ELBOs AISTATS 2024
Scores for Learning Discrete Causal Graphs with Unobserved Confounders AAAI 2024
Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces II: non-compact symmetric spaces JMLR 2024
Submodular information selection for hypothesis testing with misclassification penalties L4DC 2024
Bayesian Online Learning for Consensus Prediction AISTATS 2024
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models AAAI 2024
PAC-Bayes-Chernoff bounds for unbounded losses NIPS 2024
On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models NIPS 2024
Truthful High Dimensional Sparse Linear Regression NIPS 2024
Sample Efficient Bayesian Learning of Causal Graphs from Interventions NIPS 2024
Root Cause Explanation of Outliers under Noisy Mechanisms AAAI 2024
Sparse Variational Student-t Processes AAAI 2024
Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling JMLR 2024