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The Schr\"odinger bridge problem (SBP) is gaining increasing attention in generative modeling and showing promising potential even in comparison with the score-based generative models (SGMs).
Probability Densities with Given Marginals
Kullback, S · 1968
Earlier work this paper cites.
Reverse-time diffusion equation models
Anderson, B. D · 1982
Earlier work this paper cites.
A Stochastic Estimator of the Trace of the Influence Matrix for Laplacian Smoothing Splines
Hutchinson, M. F · 1989
Earlier work this paper cites.
Image Processing via Level Set Curvature Flow
Malladi, R. and Sethian, J. A · 1995
Earlier work this paper cites.
Convergence of the Iterative Proportional Fitting Procedure
Ruschendorf, L · 1995
Earlier work this paper cites.
Forward-Backward Stochastic Differential Equations and their Applications
Ma, J. and Yong, J · 2007
Earlier work this paper cites.
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Silva, I., Moody, G., Scott, D. J., Celi, L. A., and Mark, R. G · 2012
Earlier work this paper cites.
U-Air: When Urban Air Quality Inference Meets Big Data
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Earlier work this paper cites.
Multitask Gaussian Processes for Multivariate Physiological Time-Series Analysis
Dürichen, R., Pimentel, M. A., Clifton, L., Schweikard, A., and Clifton, D. A · 2014
Earlier work this paper cites.
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Earlier work this paper cites.
Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Sohl-Dickstein, J., Weiss, E. A., Maheswaranathan, N., and Ganguli, S · 2015
Earlier work this paper cites.
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Chen, Y. and Georgiou, T · 2016
Earlier work this paper cites.
Illiquidity Premia in the Equity Options Market
Christoffersen, P., Goyenko, R., Jacobs, K., and Karoui, M · 2017
Earlier work this paper cites.
Non-convex Learning via Stochastic Gradient Langevin Dynamics: a Nonasymptotic Analysis
Raginsky, M., Rakhlin, A., and Telgarsky, M · 2017
Earlier work this paper cites.
BRITS: Bidirectional Recurrent Imputation for Time Series
Cao, W., Wang, D., Li, J., Zhou, H., Li, L., and Li, Y · 2018
Earlier work this paper cites.
Recurrent Neural Networks for Multivariate Time Series with Missing Values
Che, Z., Purushotham, S., Cho, K., Sontag, D., and Liu, Y · 2018
Earlier work this paper cites.
Modeling Long-and Short-term Temporal Patterns with Deep Neural Networks
Lai, G., Chang, W.-C., Yang, Y., and Liu, H · 2018
Earlier work this paper cites.
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models
Grathwohl, W., Chen, R. T. Q., Bettencourt, J., Sutskever, I., and Duvenaud, D · 2019
Earlier work this paper cites.
E2GAN: End-to-end Generative Adversarial Network for Multivariate time Series Imputation
Luo, Y., Zhang, Y., Cai, X., and Yuan, X · 2019
Earlier work this paper cites.
Computational Optimal Transport: With Applications to Data Science
Peyré, G. and Cuturi, M · 2019
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Latent ODEs for Irregularly-Sampled Time Series
Rubanova, Y., Chen, R. T. Q., and Duvenaud, D · 2019
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High-dimensional Multivariate Forecasting with Low Rank Gaussian Copula Processes
Salinas, D., Bohlke-Schneider, M., Callot, L., Medico, R., and Gasthaus, J · 2019
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Generative Modeling by Estimating Gradients of The Data Distribution
Song, Y. and Ermon, S · 2019
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Normalizing Kalman Filters for Multivariate Time series Analysis
de Bézenac, E., Rangapuram, S. S., Benidis, K., Bohlke-Schneider, M., Kurle, R., Stella, L., Hasson, H., Gallinari, P., and Januschowski, T · 2020
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A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
Deep Generative Learning via Schrödinger Bridge
Wang, G., Jiao, Y., Xu, Q., Wang, Y., and Yang, C · 2021
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Wasserstein Proximal Algorithms for the Schrödinger Bridge Problem: Density Control with Nonlinear Drift
Caluya, K. and Halder, A · 2022
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Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory
Chen, T., Liu, G.-H., and Theodorou, E. A · 2022
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An Adaptively Weighted Stochastic Gradient MCMC Algorithm for Monte Carlo Simulation and Global Optimization
Deng, W., Lin, G., and Liang, F · 2022
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On the Convergence Rate of Sinkhorn’s Algorithm
Ghosal, P. and Nutz, M · 2022
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GP-VAE: Deep Probabilistic Time Series Imputation
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Denoising Diffusion Probabilistic Models
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Neural Controlled Differential Equations for Irregular Time Series
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Scalable Gradients for Stochastic Differential Equations
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Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling
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Continuous Latent Process Flows
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The Flow Map of the Fokker–Planck Equation Does Not Provide Optimal Transport
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Convergence for Score-based Generative Modeling with Polynomial Complexity
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Introduction to Entropic Optimal Transport
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Stability of Schrödinger Potentials and Convergence of Sinkhorn’s Algorithm
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Neural Conservation Laws: A Divergence-Free Perspective
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Conditional Simulation Using Diffusion Schrödinger Bridges
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