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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Probabilistic Querying of Continuous-Time Event Sequences AISTATS 2023
Integrating Random Effects in Deep Neural Networks JMLR 2023
Bayesian Structure Scores for Probabilistic Circuits AISTATS 2023
Transport Elliptical Slice Sampling AISTATS 2023
The Lauritzen-Chen Likelihood For Graphical Models AISTATS 2023
Multivariate Probabilistic Monocular 3D Object Detection WACV 2023
GFlowNet Foundations JMLR 2023
Unsupervised representation learning with recognition-parametrised probabilistic models AISTATS 2023
Encoding Domain Knowledge in Multi-view Latent Variable Models: A Bayesian Approach with Structured Sparsity AISTATS 2023
Learning Markov Random Fields for Combinatorial Structures via Sampling through Lovász Local Lemma AAAI 2023
Bayesian Data Selection JMLR 2023
Regularized Joint Mixture Models JMLR 2023
The d-Separation Criterion in Categorical Probability JMLR 2023
Learning-augmented count-min sketches via Bayesian nonparametrics JMLR 2023
Contextual Stochastic Block Model: Sharp Thresholds and Contiguity JMLR 2023
Bayesian Spiked Laplacian Graphs JMLR 2023
Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data JMLR 2023
On Distance and Kernel Measures of Conditional Dependence JMLR 2023
ScanDMM: A Deep Markov Model of Scanpath Prediction for 360deg Images CVPR 2023
Statistical Inference for Noisy Incomplete Binary Matrix JMLR 2023
Learning to love diligent trolls: Accounting for rater effects in the dialogue safety task EMNLP 2023
On Uncertainty Calibration and Selective Generation in Probabilistic Neural Summarization: A Benchmark Study EMNLP 2023
Interpreting Sentiment Composition with Latent Semantic Tree ACL 2023
Multi-Relational Probabilistic Event Representation Learning via Projected Gaussian Embedding ACL 2023
HyHTM: Hyperbolic Geometry-based Hierarchical Topic Model ACL 2023