Fields- Workshop on PDE Methods in Data Science and Machine Learning
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Title: Differentiating through optimal transport
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Title: Transport transforms for signal analysis an machine learning
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Title: Transport transforms for signal analysis and machine learning - III
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Title: Wasserstein Isometric Mapping for Image Manifold Learning
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Title: Signed Cumulative Distribution Transform for Machine Learning in 1D
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Title: Error analysis on the initial state reconstruction problem
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Title: Transport type metrics on the space of probability measures involving singular base measures
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Title: Uncertainty Principle and PDEs
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Title: Dynamical sampling for differential equations
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Title: Transport transforms for signal analysis and machine learning - II
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Title: Transport transforms for signal analysis and machine learning - I
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Title: Data-driven entropic spatially inhomogeneous evolutionary games
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Title: Sliced mutual information: a scalable measure of statistical dependence
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Title: Sparse Random Mode Decomposition
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Title: Correcting the Bias in Laplace Learning at Low Label Rates: From Laplace's to Poisson's Equation
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Title: Pattern formation in particle systems: from spherical shells to regular simplices
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Title: Spectrograms of signals impacted by noise, and their zeros
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Title: Geometric Models for Datasets and Probability Measures
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Title: Graph-based Active Learning
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Title: PDE-inspired Graph Based Methods for Machine Learning
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