marginal distribution

Hyperbolic Belief Propagation UAI 2026 Relatively Smart: A New Approach for Instance-Optimal Learning COLT 2026 Do PAC-Learners Learn the Marginal Distribution? ALT 2025 Flexible Copula-Based Mixed Models in Deep Learning: A Scalable Approach to Arbitrary Marginals AISTATS 2025 GiFT: Gibbs Fine-Tuning for Code Generation ACL 2025 Reducing Confounding Bias without Data Splitting for Causal Inference via Optimal Transport ICML 2025 Nonparametric Copula Models for Multivariate, Mixed, and Missing Data JMLR 2024 On Tail Decay Rate Estimation of Loss Function Distributions JMLR 2024 Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders ICML 2024 LinSATNet: The Positive Linear Satisfiability Neural Networks ICML 2023 Semi-Implicit Denoising Diffusion Models (SIDDMs) NeurIPS 2023 Squared Neural Families: A New Class of Tractable Density Models NeurIPS 2023 Statistical Theory of Differentially Private Marginal-based Data Synthesis Algorithms ICLR 2023 Marginal Distribution Adaptation for Discrete Sets via Module-Oriented Divergence Minimization ICML 2022 On the Learning of Non-Autoregressive Transformers ICML 2022 Adapting Event Extractors to Medical Data: Bridging the Covariate Shift EACL 2021 Domain Generalization by Marginal Transfer Learning JMLR 2021 Probabilistic Programs with Stochastic Conditioning ICML 2021 ACFlow: Flow Models for Arbitrary Conditional Likelihoods ICML 2020 ASR-Free Pronunciation Assessment Interspeech 2020 Regularized Gaussian Belief Propagation with Nodes of Arbitrary Size JMLR 2020 Steady State Analysis of Episodic Reinforcement Learning NeurIPS 2020 Belief Propagation: Accurate Marginals or Accurate Partition Function – Where is the Difference? UAI 2019 Fast and Flexible Inference of Joint Distributions from their Marginals ICML 2019 Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language NeurIPS 2018