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TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular
  Dynamics

TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics

9 February 2020
Alexander Tong
Jessie Huang
Guy Wolf
David van Dijk
Smita Krishnaswamy
ArXivPDFHTML

Papers citing "TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics"

25 / 25 papers shown
Title
Minimum-Excess-Work Guidance
Minimum-Excess-Work Guidance
Christopher Kolloff
Tobias Höppe
Emmanouil Angelis
Mathias Jacob Schreiner
Stefan Bauer
Andrea Dittadi
Simon Olsson
OT
41
0
0
19 May 2025
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
66
0
0
10 Jan 2025
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
63
4
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
169
9
0
01 Oct 2024
Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling
Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling
Mohammad R. Rezaei
Rahul G. Krishnan
Milos R. Popovic
M. Lankarany
DiffM
38
0
0
22 Sep 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
78
11
0
26 Aug 2024
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
Partially Observed Trajectory Inference using Optimal Transport and a Dynamics Prior
Anming Gu
Edward Chien
Kristjan Greenewald
55
7
0
11 Jun 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
50
1
0
30 May 2024
Computing high-dimensional optimal transport by flow neural networks
Computing high-dimensional optimal transport by flow neural networks
Chen Xu
Xiuyuan Cheng
Yao Xie
OT
59
5
0
19 May 2023
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
91
42,038
0
03 Dec 2019
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise
Xuanqing Liu
Tesi Xiao
Si Si
Qin Cao
Sanjiv Kumar
Cho-Jui Hsieh
48
134
0
05 Jun 2019
A Direct $\tilde{O}(1/ε)$ Iteration Parallel Algorithm for
  Optimal Transport
A Direct O~(1/ε)\tilde{O}(1/ε)O~(1/ε) Iteration Parallel Algorithm for Optimal Transport
A. Jambulapati
Aaron Sidford
Kevin Tian
OT
16
21
0
03 Jun 2019
Subspace Detours: Building Transport Plans that are Optimal on Subspace
  Projections
Subspace Detours: Building Transport Plans that are Optimal on Subspace Projections
Boris Muzellec
Marco Cuturi
OT
34
31
0
24 May 2019
Generalized Sliced Wasserstein Distances
Generalized Sliced Wasserstein Distances
Soheil Kolouri
Kimia Nadjahi
Umut Simsekli
Roland Badeau
Gustavo K. Rohde
21
296
0
01 Feb 2019
Scalable Unbalanced Optimal Transport using Generative Adversarial
  Networks
Scalable Unbalanced Optimal Transport using Generative Adversarial Networks
Karren D. Yang
Caroline Uhler
GAN
OT
32
75
0
26 Oct 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative
  Models
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
Will Grathwohl
Ricky T. Q. Chen
J. Bettencourt
Ilya Sutskever
David Duvenaud
DRL
40
861
0
02 Oct 2018
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
168
5,024
0
19 Jun 2018
Computational Optimal Transport
Computational Optimal Transport
Gabriel Peyré
Marco Cuturi
OT
99
2,133
0
01 Mar 2018
Geometry-Based Data Generation
Geometry-Based Data Generation
Ofir Lindenbaum
Jay S. Stanley
Guy Wolf
Smita Krishnaswamy
30
31
0
14 Feb 2018
Sharp asymptotic and finite-sample rates of convergence of empirical
  measures in Wasserstein distance
Sharp asymptotic and finite-sample rates of convergence of empirical measures in Wasserstein distance
Jonathan Niles-Weed
Francis R. Bach
72
417
0
01 Jul 2017
Masked Autoregressive Flow for Density Estimation
Masked Autoregressive Flow for Density Estimation
George Papamakarios
Theo Pavlakou
Iain Murray
80
1,340
0
19 May 2017
Improving Variational Inference with Inverse Autoregressive Flow
Improving Variational Inference with Inverse Autoregressive Flow
Diederik P. Kingma
Tim Salimans
Rafal Jozefowicz
Xi Chen
Ilya Sutskever
Max Welling
BDL
DRL
72
1,805
0
15 Jun 2016
Variational Inference with Normalizing Flows
Variational Inference with Normalizing Flows
Danilo Jimenez Rezende
S. Mohamed
DRL
BDL
210
4,143
0
21 May 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
316
149,474
0
22 Dec 2014
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation
  Distances
Sinkhorn Distances: Lightspeed Computation of Optimal Transportation Distances
Marco Cuturi
OT
78
4,210
0
04 Jun 2013
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