conftrace_

Bayesian & Probabilistic

4,733 papers (2 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Probabilistic Modeling (2,617) Variational Inference (898) Gaussian Processes (666) Bayesian Learning (483) Markov Chain Monte Carlo (374) Bayesian Optimization (284) Nonparametric Bayesian (174) Bayesian Networks (149) Conditional Random Fields (39)

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Papers (including subtopics)

Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length JMLR 2024 Graph Bayesian Optimization for Multiplex Influence Maximization AAAI 2024 Graph Neural Networks Do Not Always Oversmooth NeurIPS 2024 Grey-Box Bayesian Optimization for Sensor Placement in Assisted Living Environments AAAI 2024 Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models NeurIPS 2024 Hard Regularization to Prevent Deep Online Clustering Collapse without Data Augmentation AAAI 2024 HHD-GP: Incorporating Helmholtz-Hodge Decomposition into Gaussian Processes for Learning Dynamical Systems NeurIPS 2024 Hodge-Compositional Edge Gaussian Processes AISTATS 2024 Identifiability of Product of Experts Models AISTATS 2024 Identifiable Object-Centric Representation Learning via Probabilistic Slot Attention NeurIPS 2024 Identification of mixtures of discrete product distributions in near-optimal sample and time complexity COLT 2024 Identifying and Addressing Disparities in Public Libraries with Bayesian Latent Variable Modeling AAAI 2024 Identifying Homogeneous and Interpretable Groups for Conformal Prediction UAI 2024 Idiographic Personality Gaussian Process for Psychological Assessment NeurIPS 2024 Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations NeurIPS 2024 Improved off-policy training of diffusion samplers NeurIPS 2024 Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes NeurIPS 2024 Inconsistency of Cross-Validation for Structure Learning in Gaussian Graphical Models AISTATS 2024 Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data AAAI 2024 Inferring stochastic low-rank recurrent neural networks from neural data NeurIPS 2024 Interpretability Guarantees with Merlin-Arthur Classifiers AISTATS 2024 Interventional Causal Discovery in a Mixture of DAGs NeurIPS 2024 Intervention and Conditioning in Causal Bayesian Networks NeurIPS 2024 Intrinsic Gaussian Vector Fields on Manifolds AISTATS 2024 Inversion-based Latent Bayesian Optimization NeurIPS 2024