Probabilistic Modeling

Nonstationary Sparse Spectral Permanental Process NeurIPS 2024 Normalizing Flows on the Product Space of SO(3) Manifolds for Probabilistic Human Pose Modeling CVPR 2024 On Divergence Measures for Training GFlowNets NeurIPS 2024 One Sample Fits All: Approximating All Probabilistic Values Simultaneously and Efficiently NeurIPS 2024 On Hardware-efficient Inference in Probabilistic Circuits UAI 2024 On Neural Networks as Infinite Tree-Structured Probabilistic Graphical Models NeurIPS 2024 On Regularized Radon-Nikodym Differentiation JMLR 2024 On the connection between Noise-Contrastive Estimation and Contrastive Divergence AISTATS 2024 On the Expressive Power of Tree-Structured Probabilistic Circuits NeurIPS 2024 Optimal estimation of Gaussian (poly)trees AISTATS 2024 Parallel-in-Time Probabilistic Numerical ODE Solvers JMLR 2024 Partial identification of the maximum mean discrepancy with mismeasured data UAI 2024 Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning NeurIPS 2024 PGMax: Factor Graphs for Discrete Probabilistic Graphical Models and Loopy Belief Propagation in JAX JMLR 2024 Piecewise deterministic generative models NeurIPS 2024 Poisson Variational Autoencoder NeurIPS 2024 Preferential Normalizing Flows NeurIPS 2024 PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model AISTATS 2024 Probabilistic Integral Circuits AISTATS 2024 Probabilistic Modeling for Sequences of Sets in Continuous-Time AISTATS 2024 Probabilistic Neural Circuits AAAI 2024 Probabilistic reconciliation of mixed-type hierarchical time series UAI 2024 Probabilistic size-and-shape functional mixed models NeurIPS 2024 Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks NeurIPS 2024 Qualitative Mechanism Independence NeurIPS 2024