sampling algorithm

City Sampling for Citizens’ Assemblies AAAI 2026 Functional Stochastic Localization COLT 2026 How I Met Your Bias: Investigating Bias Amplification in Diffusion Models WACV 2026 Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation JMLR 2025 Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel ICLR 2025 Improved Sampling Algorithms for Lévy-Itô Diffusion Models ICLR 2025 Langevin Monte Carlo Beyond Lipschitz Gradient Continuity AAAI 2025 NoiseCtrl: A Sampling-Algorithm-Agnostic Conditional Generation Method for Diffusion Models CVPR 2025 Quantum (Inspired) D^2-sampling with Applications ICLR 2025 Statistical Significance of Feature Importance Rankings UAI 2025 A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers NeurIPS 2024 Chain of Log-Concave Markov Chains ICLR 2024 Efficient Dependency Tree Sampling Without Replacement NAACL 2024 Fast Dynamic Sampling for Determinantal Point Processes AISTATS 2024 Fast Sampling via Discrete Non-Markov Diffusion Models with Predetermined Transition Time NeurIPS 2024 Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding ACL 2024 Geometric No-U-Turn Samplers: Concepts and Evaluation PGM 2024 Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models NeurIPS 2024 In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies NeurIPS 2024 Local and Global Decoding in Text Generation EMNLP 2024 Non-geodesically-convex optimization in the Wasserstein space NeurIPS 2024 Promoting Fairness Among Dynamic Agents in Online-Matching Markets under Known Stationary Arrival Distributions NeurIPS 2024 Reverse Transition Kernel: A Flexible Framework to Accelerate Diffusion Inference NeurIPS 2024 A Faster Sampler for Discrete Determinantal Point Processes AISTATS 2023 Computing (1+epsilon)-Approximate Degeneracy in Sublinear Time IJCAI 2023