Probabilistic Modeling

Better-than-KL PAC-Bayes Bounds COLT 2024 Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support AISTATS 2024 Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding NeurIPS 2024 Big Learning Expectation Maximization AAAI 2024 Breaking the curse of dimensionality in structured density estimation NeurIPS 2024 Bridge-IF: Learning Inverse Protein Folding with Markov Bridges NeurIPS 2024 Building Expressive and Tractable Probabilistic Generative Models: A Review IJCAI 2024 Cascade of phase transitions in the training of energy-based models NeurIPS 2024 Categorical Flow Matching on Statistical Manifolds NeurIPS 2024 Cauchy Graphical Models PGM 2024 CausalCite: A Causal Formulation of Paper Citations ACL 2024 Causal Discovery from Poisson Branching Structural Causal Model Using High-Order Cumulant with Path Analysis AAAI 2024 Causal Effect Identification in a Sub-Population with Latent Variables NeurIPS 2024 Chain of Log-Concave Markov Chains ICLR 2024 Classification Diffusion Models: Revitalizing Density Ratio Estimation NeurIPS 2024 Classifier Calibration with ROC-Regularized Isotonic Regression AISTATS 2024 Collaborative Synthesis of Patient Records through Multi-Visit Health State Inference AAAI 2024 Colour Passing Revisited: Lifted Model Construction with Commutative Factors AAAI 2024 Combining Statistical Depth and Fermat Distance for Uncertainty Quantification NeurIPS 2024 Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference NeurIPS 2024 Conditional Bayesian Quadrature UAI 2024 Conformal Autoregressive Generation: Beam Search with Coverage Guarantees AAAI 2024 Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting AAAI 2024 Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors AISTATS 2024 Constrained Sampling with Primal-Dual Langevin Monte Carlo NeurIPS 2024