constrained sampling

Accelerating Constrained Sampling: A Large Deviations Approach JMLR 2026 Higher-Order Hit-&-Run Samplers for Linearly Constrained Densities UAI 2026 Better than Random: Reliable NLG Human Evaluation with Constrained Active Sampling AAAI 2024 Constrained Sampling with Primal-Dual Langevin Monte Carlo NeurIPS 2024 Fast sampling from constrained spaces using the Metropolis-adjusted Mirror Langevin algorithm COLT 2024 Functional Gradient Flows for Constrained Sampling NeurIPS 2024 Penalized Overdamped and Underdamped Langevin Monte Carlo Algorithms for Constrained Sampling JMLR 2024 Converge to the Truth: Factual Error Correction via Iterative Constrained Editing AAAI 2023 Learning Rate Free Sampling in Constrained Domains NeurIPS 2023 MotionDiffuser: Controllable Multi-Agent Motion Prediction Using Diffusion CVPR 2023 Sampling with Mollified Interaction Energy Descent ICLR 2023 Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo NeurIPS 2023 Counting, Sampling, and Synthesis: The Quest for Scalability IJCAI 2022 Gradient-based Constrained Sampling from Language Models EMNLP 2022 Sampling in Constrained Domains with Orthogonal-Space Variational Gradient Descent NeurIPS 2022 Sampling with Riemannian Hamiltonian Monte Carlo in a Constrained Space NeurIPS 2022 WordTies: Measuring Word Associations in Language Models via Constrained Sampling EMNLP 2022 Back-translation for Large-Scale Multilingual Machine Translation EMNLP 2021 Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning COLT 2021 Sampling with Trusthworthy Constraints: A Variational Gradient Framework NeurIPS 2021 Flexible sampling of discrete data correlations without the marginal distributions NeurIPS 2013 What do row and column marginals reveal about your dataset? NeurIPS 2013