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Manifold Interpolating Optimal-Transport Flows for Trajectory Inference

Manifold Interpolating Optimal-Transport Flows for Trajectory Inference

29 June 2022
G. Huguet
D. S. Magruder
Alexander Tong
O. Fasina
Manik Kuchroo
Guy Wolf
Smita Krishnaswamy
    OT
    DRL
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Papers citing "Manifold Interpolating Optimal-Transport Flows for Trajectory Inference"

11 / 11 papers shown
Title
Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems
Using Linearized Optimal Transport to Predict the Evolution of Stochastic Particle Systems
Nicholas Karris
Evangelos A. Nikitopoulos
Ioannis G. Kevrekidis
Seungjoon Lee
Alexander Cloninger
OT
35
0
0
10 Jan 2025
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
Y. Lin
Ronald R. Coifman
Gal Mishne
Ronen Talmon
38
2
0
28 Oct 2024
Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds
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
36
3
0
16 Oct 2024
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport
Learning stochastic dynamics from snapshots through regularized unbalanced optimal transport
Zhenyi Zhang
Tiejun Li
Peijie Zhou
OT
141
5
0
01 Oct 2024
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold
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
31
5
0
26 Aug 2024
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging
Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging
Amartya Banerjee
Harlin Lee
Nir Sharon
Caroline Moosmüller
34
1
0
30 May 2024
Neural FIM for learning Fisher Information Metrics from point cloud data
Neural FIM for learning Fisher Information Metrics from point cloud data
O. Fasina
Guilluame Huguet
Alexander Tong
Yanlei Zhang
Guy Wolf
Maximilian Nickel
Ian M. Adelstein
Smita Krishnaswamy
22
3
0
01 Jun 2023
Deep Momentum Multi-Marginal Schrödinger Bridge
Deep Momentum Multi-Marginal Schrödinger Bridge
T. Chen
Guan-Horng Liu
Molei Tao
Evangelos A. Theodorou
15
9
0
03 Mar 2023
Neural Conservation Laws: A Divergence-Free Perspective
Neural Conservation Laws: A Divergence-Free Perspective
Jack Richter-Powell
Y. Lipman
Ricky T. Q. Chen
35
49
0
04 Oct 2022
Neural Lagrangian Schrödinger Bridge: Diffusion Modeling for
  Population Dynamics
Neural Lagrangian Schrödinger Bridge: Diffusion Modeling for Population Dynamics
Takeshi Koshizuka
Issei Sato
20
6
0
11 Apr 2022
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold
  heat interpolation
Eigen-convergence of Gaussian kernelized graph Laplacian by manifold heat interpolation
Xiuyuan Cheng
Nan Wu
55
29
0
25 Jan 2021
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