multimodal distribution

Flow Matching for Multimodal Distributions CVPR 2026 Efficiently learning and sampling multimodal distributions with data-based initialization COLT 2025 Enhancing Knowledge Distillation of Large Language Models through Efficient Multi-Modal Distribution Alignment COLING 2025 Geodesic Slice Sampler for Multimodal Distributions with Strong Curvature UAI 2025 Hierarchical Light Transformer Ensembles for Multimodal Trajectory Forecasting WACV 2025 Importance Corrected Neural JKO Sampling ICML 2025 Learned Reference-based Diffusion Sampler for multi-modal distributions ICLR 2025 Maximum Entropy Reinforcement Learning with Diffusion Policy ICML 2025 Provable Convergence and Limitations of Geometric Tempering for Langevin Dynamics ICLR 2025 TAROT: Targeted Data Selection via Optimal Transport ICML 2025 Toward Near-Globally Optimal Nonlinear Model Predictive Control via Diffusion Models L4DC 2025 Adaptive Multi-Modal Cross-Entropy Loss for Stereo Matching CVPR 2024 Diffusive Gibbs Sampling ICML 2024 FlowBotHD: History-Aware Diffuser Handling Ambiguities in Articulated Objects Manipulation CoRL 2024 Gradient-based Discrete Sampling with Automatic Cyclical Scheduling NeurIPS 2024 ROME: Robust Multi-Modal Density Estimator IJCAI 2024 Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization ICLR 2024 Stochastic Localization via Iterative Posterior Sampling ICML 2024 Adaptive Conditional Quantile Neural Processes UAI 2023 An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions NeurIPS 2023 Directed Chain Generative Adversarial Networks ICML 2023 Flow Annealed Importance Sampling Bootstrap ICLR 2023 GFlowNets and variational inference ICLR 2023 Imitating Human Behaviour with Diffusion Models ICLR 2023 Large Language Models Are Zero-Shot Time Series Forecasters NeurIPS 2023