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Single-cell genomics has significantly advanced our understanding of cellular behavior, catalyzing innovations in treatments and precision medicine.
On the transfer of masses (in russian)
L Kantorovich · 1942
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Stochastic gene expression in a single cell
Michael B Elowitz, Arnold J Levine, Eric D Siggia, and Peter S Swain · 2002
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Foundations of Modern Probability
Olav Kallenberg · 2002
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Numerical resolution of an “unbalanced” mass transport problem
Jean-David Benamou · 2003
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Gromov–wasserstein distances and the metric approach to object matching
Facundo Mémoli · 2011
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Geodesics in heat: A new approach to computing distance based on heat flow
Keenan Crane, Clarisse Weischedel, and Max Wardetzky · 2013
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Sinkhorn Distances: Lightspeed Computation of Optimal Transport
Marco Cuturi · 2013
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A survey of the schrödinger problem and some of its connections with optimal transport, 2013
Christian Léonard · 2013
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A numerical method to solve optimal transport problems with coulomb cost, 2015
Jean-David Benamou, Guillaume Carlier, and Luca Nenna · 2015
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Learning with a wasserstein loss
Charlie Frogner, Chiyuan Zhang, Hossein Mobahi, Mauricio Araya, and Tomaso A Poggio · 2015
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Optimal Transport for Applied Mathematicians
Filippo Santambrogio · 2015
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Convolutional wasserstein distances: Efficient optimal transportation on geometric domains
Justin Solomon, Fernando De Goes, Gabriel Peyré, Marco Cuturi, Adrian Butscher, Andy Nguyen, Tao Du, and Leonidas Guibas · 2015
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Gromov-wasserstein averaging of kernel and distance matrices
Gabriel Peyré, Marco Cuturi, and Justin Solomon · 2016
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The human cell atlas
Aviv Regev, Sarah A Teichmann, Eric S Lander, Ido Amit, Christophe Benoist, Ewan Birney, Bernd Bodenmiller, Peter Campbell, Piero Carninci, Menna Clatworthy, et al · 2017
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Large-scale optimal transport and mapping estimation
Vivien Seguy, Bharath Bhushan Damodaran, Rémi Flamary, Nicolas Courty, Antoine Rolet, and Mathieu Blondel · 2017
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Jonathan Weed and Francis Bach · 2017
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Gromov-wasserstein alignment of word embedding spaces
David Alvarez-Melis and Tommi S Jaakkola · 2018
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JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 2018
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Neural ordinary differential equations
Ricky TQ Chen, Yulia Rubanova, Jesse Bettencourt, and David K Duvenaud · 2018
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Unbalanced optimal transport: geometry and Kantorovich formulation
Lenaic Chizat, Gabriel Peyré, Bernhard Schmitzer, and François-Xavier Vialard · 2018
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Optimal entropy-transport problems and a new hellinger–kantorovich distance between positive measures
Matthias Liero, Alexander Mielke, and Giuseppe Savaré · 2018
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Umap: Uniform manifold approximation and projection for dimension reduction
Leland McInnes, John Healy, and James Melville · 2018
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Manifold learning-based methods for analyzing single-cell rna-sequencing data
Kevin R Moon, Jay S Stanley III, Daniel Burkhardt, David van Dijk, Guy Wolf, and Smita Krishnaswamy · 2018
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Optimal transport for structured data with application on graphs
Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, and Nicolas Courty · 2018
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Comprehensive single cell mrna profiling reveals a detailed roadmap for pancreatic endocrinogenesis
Aimée Bastidas-Ponce, Sophie Tritschler, Leander Dony, Katharina Scheibner, Marta Tarquis-Medina, Ciro Salinno, Silvia Schirge, Ingo Burtscher, Anika Böttcher, Fabian J Theis, et al · 2019
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Interpolating between Optimal Transport and MMD using Sinkhorn Divergences
Jean Feydy, Thibault Séjourné, François-Xavier Vialard, Shun-Ichi Amari, Alain Trouvé, and Gabriel Peyré · 2019
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Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming
Geoffrey Schiebinger, Jian Shu, Marcin Tabaka, Brian Cleary, Vidya Subramanian, Aryeh Solomon, Joshua Gould, Siyan Liu, Stacie Lin, Peter Berube, et al · 2019
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Entropic optimal transport between unbalanced gaussian measures has a closed form
Hicham Janati, Boris Muzellec, Gabriel Peyré, and Marco Cuturi · 2020
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Massively multiplex chemical transcriptomics at single-cell resolution
Sanjay R Srivatsan, José L McFaline-Figueroa, Vijay Ramani, Lauren Saunders, Junyue Cao, Jonathan Packer, Hannah A Pliner, Dana L Jackson, Riza M Daza, Lena Christiansen, et al · 2020
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TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Alexander Tong, Jessie Huang, Guy Wolf, David Van Dijk, and Smita Krishnaswamy · 2020
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Lineage tracing meets single-cell omics: opportunities and challenges
Daniel E Wagner and Allon M Klein · 2020
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Learning Single-Cell Perturbation Responses using Neural Optimal Transport
Charlotte Bunne, Stefan G Stark, Gabriele Gut, Jacobo Sarabia del Castillo, Kjong-Van Lehmann, Lucas Pelkmans, Andreas Krause, and Gunnar Ratsch · 2021
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Likelihood training of schr \ \backslash " odinger bridge using forward-backward sdes theory
Tianrong Chen, Guan-Horng Liu, and Evangelos A Theodorou · 2021
On the sample complexity of entropic optimal transport, 2022
Philippe Rigollet and Austin J. Stromme · 2022
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Linear-time gromov wasserstein distances using low rank couplings and costs
Meyer Scetbon, Gabriel Peyré, and Marco Cuturi · 2022
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Unbalanced optimal transport, from theory to numerics
Thibault Séjourné, Gabriel Peyré, and François-Xavier Vialard · 2022
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Augmented bridge matching, 2023
Valentin De Bortoli, Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou, and Weilie Nie · 2023
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Causal identification of single-cell experimental perturbation effects with cinema-ot
Mingze Dong, Bao Wang, Jessica Wei, Antonio H de O. Fonseca, Curtis J Perry, Alexander Frey, Feriel Ouerghi, Ellen F Foxman, Jeffrey J Ishizuka, Rahul M Dhodapkar, et al · 2023
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Score-based generative neural networks for large-scale optimal transport
Max Daniels, Tyler Maunu, and Paul Hand · 2021
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Diffusion schrödinger bridge with applications to score-based generative modeling
Valentin De Bortoli, James Thornton, Jeremy Heng, and Arnaud Doucet · 2021
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Minibatch optimal transport distances; analysis and applications
Kilian Fatras, Younes Zine, Szymon Majewski, Rémi Flamary, Rémi Gribonval, and Nicolas Courty · 2021
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A roadmap for the human developmental cell atlas
Muzlifah Haniffa, Deanne Taylor, Sten Linnarsson, Bruce J Aronow, Gary D Bader, Roger A Barker, Pablo G Camara, J Gray Camp, Alain Chédotal, Andrew Copp, et al · 2021
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A sandbox for prediction and integration of dna, rna, and proteins in single cells
Malte D Luecken, Daniel Bernard Burkhardt, Robrecht Cannoodt, Christopher Lance, Aditi Agrawal, Hananeh Aliee, Ann T Chen, Louise Deconinck, Angela M Detweiler, Alejandro A Granados, et al · 2021
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Entropic estimation of optimal transport maps
Aram-Alexandre Pooladian and Jonathan Niles-Weed · 2021
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Low-rank sinkhorn factorization
Meyer Scetbon, Marco Cuturi, and Gabriel Peyré · 2021
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Luca Eyring, Dominik Klein, Théo Uscidda, Giovanni Palla, Niki Kilbertus, Zeynep Akata, and Fabian Theis · 2023
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Nikita Gushchin, Alexander Kolesov, Petr Mokrov, Polina Karpikova, Andrey Spiridonov, Evgeny Burnaev, and Alexander Korotin · 2023
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An integrated transcriptomic cell atlas of human neural organoids
Zhisong He, Leander Dony, Jonas Simon Fleck, Artur Szalata, Katelyn X Li, Irena Sliskovic, Hsiu-Chuan Lin, Malgorzata Santel, Alexander Atamian, Giorgia Quadrato, et al · 2023
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Best practices for single-cell analysis across modalities
Lukas Heumos, Anna C Schaar, Christopher Lance, Anastasia Litinetskaya, Felix Drost, Luke Zappia, Malte D Lücken, Daniel C Strobl, Juan Henao, Fabiola Curion, et al · 2023
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Mapping cells through time and space with moscot
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Light schrödinger bridge, 2023
Alexander Korotin, Nikita Gushchin, and Evgeny Burnaev · 2023
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Mapping lineage-traced cells across time points with moslin
Marius Lange, Zoe Piran, Michal Klein, Bastiaan Spanjaard, Dominik Klein, Jan Philipp Junker, Fabian J Theis, and Mor Nitzan · 2023
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Flow matching for generative modeling, 2023
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matt Le · 2023
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I 2 sb: Image-to-image schrödinger bridge, 2023
Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, and Anima Anandkumar · 2023
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Energy-guided entropic neural optimal transport
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Neural gromov-wasserstein optimal transport
Maksim Nekrashevich, Alexander Korotin, and Evgeny Burnaev · 2023
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Diffusion bridge mixture transports, schrödinger bridge problems and generative modeling, 2023
Stefano Peluchetti · 2023
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Multisample flow matching: Straightening flows with minibatch couplings
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Entropic gromov-wasserstein distances: Stability, algorithms, and distributional limits
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Diffusion schr \ \backslash " odinger bridge matching
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Aligning individual brains with fused unbalanced gromov-wasserstein, 2023
Alexis Thual, Huy Tran, Tatiana Zemskova, Nicolas Courty, Rémi Flamary, Stanislas Dehaene, and Bertrand Thirion · 2023
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The monge gap: A regularizer to learn all transport maps, 2023
Théo Uscidda and Marco Cuturi · 2023
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Unified fate mapping in multiview single-cell data
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Gromov-wasserstein distances: Entropic regularization, duality, and sample complexity, 2023
Zhengxin Zhang, Ziv Goldfeld, Youssef Mroueh, and Bharath K. Sriperumbudur · 2023
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Denoising diffusion bridge models, 2023
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Light unbalanced optimal transport, 2024
Milena Gazdieva, Arip Asadulaev, Alexander Korotin, and Evgeny Burnaev · 2024
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Unbalanced low-rank optimal transport solvers
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Neural estimation of entropic optimal transport, 2024
Tao Wang and Ziv Goldfeld · 2024
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