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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Collaborative Uncertainty in Multi-Agent Trajectory Forecasting NIPS 2021
Uncertain-aware Safe Exploratory Planning using Gaussian Process and Neural Control Contraction Metric L4DC 2021
Continuous-time edge modelling using non-parametric point processes NIPS 2021
Lifted reasoning meets weighted model integration UAI 2021
Approximate implication with d-separation UAI 2021
A Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference NIPS 2021
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting NIPS 2021
A Structured Observation Distribution for Generative Biological Sequence Prediction and Forecasting ICML 2021
Autoencoding Under Normalization Constraints ICML 2021
Learning Bayesian Networks from Ordinal Data JMLR 2021
Reproducing kernel Hilbert C*-module and kernel mean embeddings JMLR 2021
Whittle Networks: A Deep Likelihood Model for Time Series ICML 2021
Deep Gaussian Scale Mixture Prior for Spectral Compressive Imaging CVPR 2021
Predictive Learning on Hidden Tree-Structured Ising Models JMLR 2021
Asymptotic Normality, Concentration, and Coverage of Generalized Posteriors JMLR 2021
A Bayesian Contiguous Partitioning Method for Learning Clustered Latent Variables JMLR 2021
Integrated Principal Components Analysis JMLR 2021
Soft Tensor Regression JMLR 2021
Probabilistic Generating Circuits ICML 2021
Affective Processes: Stochastic Modelling of Temporal Context for Emotion and Facial Expression Recognition CVPR 2021
Nonparametric Hamiltonian Monte Carlo ICML 2021
SGA: A Robust Algorithm for Partial Recovery of Tree-Structured Graphical Models with Noisy Samples ICML 2021
Probabilistic, Structure-Aware Algorithms for Improved Variety, Accuracy, and Coverage of AMR Alignments ACL 2021
Kernel Stein Discrepancy Descent ICML 2021
Avoiding Kernel Fixed Points: Computing with ELU and GELU Infinite Networks AAAI 2021