A Computational Framework for Solving Wasserstein Lagrangian Flows

16 October 2023

Papers citing "A Computational Framework for Solving Wasserstein Lagrangian Flows"

21 / 21 papers shown

Title
PINN-MEP: Continuous Neural Representations for Minimum-Energy Path Discovery in Molecular Systems Magnus Petersen Roberto Covino 120 0 0 23 Apr 2025
Generalized Flow Matching for Transition Dynamics Modeling Haibo Wang Yuxuan Qiu Yanze Wang Rob Brekelmans Yuanqi Du 29 1 0 19 Oct 2024
Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds Xingzhi Sun Danqi Liao Kincaid MacDonald Yanlei Zhang Chen Liu Guillaume Huguet Guy Wolf Ian M. Adelstein Tim G. J. Rudner Smita Krishnaswamy 46 3 0 16 Oct 2024
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling Yuanqi Du Michael Plainer Rob Brekelmans Chenru Duan Frank Noé Carla P. Gomes Alán Aspuru-Guzik Kirill Neklyudov 37 9 0 10 Oct 2024
Scalable Simulation-free Entropic Unbalanced Optimal Transport Jaemoo Choi Jaewoong Choi OT 23 0 0 03 Oct 2024
Improving Neural Optimal Transport via Displacement Interpolation Jaemoo Choi Yongxin Chen Jaewoong Choi OT 43 0 0 03 Oct 2024
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport Zhenyi Zhang Tiejun Li Peijie Zhou OT 143 5 0 01 Oct 2024
Score-based Neural Ordinary Differential Equations for Computing Mean Field Control Problems Mo Zhou Stanley Osher Wuchen Li 84 2 0 24 Sep 2024
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold Lazar Atanackovic Xi Zhang Brandon Amos Mathieu Blanchette Leo J. Lee Yoshua Bengio Alexander Tong Kirill Neklyudov 33 5 0 26 Aug 2024
Neural Optimal Transport with Lagrangian Costs Aram-Alexandre Pooladian Carles Domingo-Enrich Ricky T. Q. Chen Brandon Amos OT 40 15 0 01 Jun 2024
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging Amartya Banerjee Harlin Lee Nir Sharon Caroline Moosmüller 42 1 0 30 May 2024
Metric Flow Matching for Smooth Interpolations on the Data Manifold Kacper Kapusniak Peter Potaptchik Teodora Reu Leo Zhang Alexander Tong Michael M. Bronstein A. Bose Francesco Di Giovanni 39 11 0 23 May 2024
Dynamic Conditional Optimal Transport through Simulation-Free Flows Gavin Kerrigan Giosue Migliorini Padhraic Smyth OT 38 10 0 05 Apr 2024
Multisample Flow Matching: Straightening Flows with Minibatch Couplings Aram-Alexandre Pooladian Heli Ben-Hamu Carles Domingo-Enrich Brandon Amos Y. Lipman Ricky T. Q. Chen 60 126 0 28 Apr 2023
Stochastic Interpolants: A Unifying Framework for Flows and Diffusions M. S. Albergo Nicholas M. Boffi Eric Vanden-Eijnden DiffM 248 261 0 15 Mar 2023
Rectified Flow: A Marginal Preserving Approach to Optimal Transport Qiang Liu OT 130 85 0 29 Sep 2022
Riemannian Metric Learning via Optimal Transport Christopher Scarvelis Justin Solomon OT 40 11 0 18 May 2022
Variational Wasserstein gradient flow JiaoJiao Fan Qinsheng Zhang Amirhossein Taghvaei Yongxin Chen 72 54 0 04 Dec 2021
Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory T. Chen Guan-Horng Liu Evangelos A. Theodorou DiffM OT 174 162 0 21 Oct 2021
Towards a mathematical theory of trajectory inference Hugo Lavenant Stephen X. Zhang Young-Heon Kim Geoffrey Schiebinger 21 40 0 18 Feb 2021
Input Convex Neural Networks Brandon Amos Lei Xu J. Zico Kolter 175 597 0 22 Sep 2016