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Bayesian Inference

1724 directly classified papers

Papers per year

Papers

Fine-Grained Change Point Detection for Topic Modeling with Pitman-Yor Process JMLR 2025
Sampling and Estimation on Manifolds using the Langevin Diffusion JMLR 2025
On Consistent Bayesian Inference from Synthetic Data JMLR 2025
Language-Informed Synthesis of Rational Agent Models for Grounded Theory-of-Mind Reasoning On-the-fly EMNLP 2025
REALM: Recursive Relevance Modeling for LLM-based Document Re-Ranking EMNLP 2025
Scalable and Adaptive Variational Bayes Methods for Hawkes Processes JMLR 2025
Combining Climate Models using Bayesian Regression Trees and Random Paths JMLR 2025
Bayesian Score Calibration for Approximate Models JMLR 2025
Langevin Monte Carlo Beyond Lipschitz Gradient Continuity AAAI 2025
New Compilation Languages Based on Restricted Weak Decomposability AAAI 2025
Leveraging Human Input to Enable Robust, Interactive, and Aligned AI Systems AAAI 2025
Quantitative Predictive Monitoring and Control for Safe Human-Machine Interaction AAAI 2025
Gaussian Process Bandits for Top-k Recommendations NIPS 2024
Intervention and Conditioning in Causal Bayesian Networks NIPS 2024
Continual learning with the neural tangent ensemble NIPS 2024
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models NIPS 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes NIPS 2024
PAC-Bayes-Chernoff bounds for unbounded losses NIPS 2024
Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts CVPR 2024
NeoRL: Efficient Exploration for Nonepisodic RL NIPS 2024
Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning NIPS 2024
Bayesian Adaptive Calibration and Optimal Design NIPS 2024
Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization NIPS 2024
Poisson Variational Autoencoder NIPS 2024
Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation NIPS 2024