{"total":33,"rows":[{"id":"2402.14017","title":"D-Flow: Differentiating through Flows for Controlled Generation","created":"2024-02-21","cited_by_count":122,"area":"diffusion"},{"id":"2405.14664","title":"Fisher Flow Matching for Generative Modeling over Discrete Data","created":"2024-05-23","cited_by_count":72,"area":"diffusion"},{"id":"2404.19739","title":"Mixed Continuous and Categorical Flow Matching for 3D De Novo Molecule Generation","created":"2024-04-30","cited_by_count":54,"area":"diffusion"},{"id":"2405.16441","title":"Categorical Flow Matching on Statistical Manifolds","created":"2024-05-26","cited_by_count":47,"area":"diffusion"},{"id":"2410.18070","title":"Training Free Guided Flow Matching with Optimal Control","created":"2024-10-23","cited_by_count":25,"area":"diffusion"},{"id":"2504.10283","title":"$\\alpha$-Flow: A Unified Framework for Continuous-State Discrete Flow Matching Models","created":"2025-04-14","cited_by_count":18,"area":"diffusion"},{"id":"2505.23346","title":"Beyond Optimal Transport: Model-Aligned Coupling for Flow Matching","created":"2025-05-29","cited_by_count":15,"area":"diffusion"},{"id":"2508.17815","title":"Multi-domain Distribution Learning for De Novo Drug Design","created":"2025-08-25","cited_by_count":15,"area":"diffusion"},{"id":"2506.10532","title":"Equivariant Neural Diffusion for Molecule Generation","created":"2025-06-12","cited_by_count":13,"area":"diffusion"},{"id":"2405.15252","title":"Accelerating 3D Molecule Generation via Jointly Geometric Optimal Transport","created":"2024-05-24","cited_by_count":11,"area":"diffusion"},{"id":"2411.16644","title":"Exploring Discrete Flow Matching for 3D De Novo Molecule Generation","created":"2024-11-25","cited_by_count":11,"area":"diffusion"},{"id":"2406.12816","title":"Neural Approximate Mirror Maps for Constrained Diffusion Models","created":"2024-06-18","cited_by_count":9,"area":"diffusion"},{"id":"2501.02526","title":"Unified Guidance for Geometry-Conditioned Molecular Generation","created":"2025-01-05","cited_by_count":9,"area":"diffusion"},{"id":"2406.10513","title":"Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space","created":"2024-06-15","cited_by_count":8,"area":"diffusion"},{"id":"2505.13791","title":"Scalable Autoregressive 3D Molecule Generation","created":"2025-05-20","cited_by_count":8,"area":"diffusion"},{"id":"2509.23822","title":"Space Group Conditional Flow Matching","created":"2025-09-28","cited_by_count":7,"area":"diffusion"},{"id":"2602.15022","title":"Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation","created":"2026-02-16","cited_by_count":7,"area":"diffusion"},{"id":"2504.08051","title":"Compositional Flows for 3D Molecule and Synthesis Pathway Co-design","created":"2025-04-10","cited_by_count":6,"area":"diffusion"},{"id":"2506.07199","title":"Audio synthesizer inversion in symmetric parameter spaces with approximately equivariant flow matching","created":"2025-06-08","cited_by_count":6,"area":"diffusion"},{"id":"2412.12540","title":"Stiefel Flow Matching for Moment-Constrained Structure Elucidation","created":"2024-12-17","cited_by_count":5,"area":"diffusion"},{"id":"2508.07102","title":"Towards High-Order Mean Flow Generative Models: Feasibility, Expressivity, and Provably Efficient Criteria","created":"2025-08-09","cited_by_count":5,"area":"diffusion"},{"id":"2512.18184","title":"Is There a Better Source Distribution than Gaussian? Exploring Source Distributions for Image Flow Matching","created":"2025-12-20","cited_by_count":5,"area":"diffusion"},{"id":"2405.05665","title":"SubGDiff: A Subgraph Diffusion Model to Improve Molecular Representation Learning","created":"2024-05-09","cited_by_count":4,"area":"diffusion"},{"id":"2502.08598","title":"Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models","created":"2025-02-12","cited_by_count":4,"area":"diffusion"},{"id":"2509.03340","title":"Equivariant Flow Matching for Symmetry-Breaking Bifurcation Problems","created":"2025-09-03","cited_by_count":4,"area":"diffusion"},{"id":"2504.15773","title":"Clifford Group Equivariant Diffusion Models for 3D Molecular Generation","created":"2025-04-22","cited_by_count":3,"area":"diffusion"},{"id":"2601.21985","title":"Elign: Equivariant Diffusion Model Alignment from Foundational Machine Learning Force Fields","created":"2026-01-29","cited_by_count":3,"area":"diffusion"},{"id":"2502.08006","title":"Greed is Good: A Unifying Perspective on Guided Generation","created":"2025-02-11","cited_by_count":2,"area":"diffusion"},{"id":"2505.21539","title":"Equivariant Flow Matching for Point Cloud Assembly","created":"2025-05-24","cited_by_count":2,"area":"diffusion"},{"id":"2510.04646","title":"Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generation","created":"2025-10-06","cited_by_count":2,"area":"diffusion"},{"id":"2511.17249","title":"FlexiFlow: decomposable flow matching for generation of flexible molecular ensemble","created":"2025-11-21","cited_by_count":2,"area":"diffusion"},{"id":"2408.15899","title":"Gen-Swarms: Adapting Deep Generative Models to Swarms of Drones","created":"2024-08-28","cited_by_count":0,"area":"diffusion"},{"id":"2604.08189","title":"Equivariant Efficient Joint Discrete and Continuous MeanFlow for Molecular Graph Generation","created":"2026-04-09","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}