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    solo-learn: A Library of Self-supervised Methods for Visual Representation Learning

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    Bayesian Pseudo Posterior Mechanism under Asymptotic Differential Privacy

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    SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

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    DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python

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    LinCDE: Conditional Density Estimation via Lindsey's Method

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    Toolbox for Multimodal Learn (scikit-multimodallearn)

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    Analytically Tractable Hidden-States Inference in Bayesian Neural Networks

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    Innovations Autoencoder and its Application in One-class Anomalous Sequence Detection

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    Overparameterization of Deep ResNet: Zero Loss and Mean-field Analysis

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    Cascaded Diffusion Models for High Fidelity Image Generation

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    Beyond Sub-Gaussian Noises: Sharp Concentration Analysis for Stochastic Gradient Descent

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    Optimal Transport for Stationary Markov Chains via Policy Iteration

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    PAC Guarantees and Effective Algorithms for Detecting Novel Categories

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    Sampling Permutations for Shapley Value Estimation

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    Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks

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    The correlation-assisted missing data estimator

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    Structure-adaptive Manifold Estimation

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    (f,Gamma)-Divergences: Interpolating between f-Divergences and Integral Probability Metrics

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    Score Matched Neural Exponential Families for Likelihood-Free Inference

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    Projected Statistical Methods for Distributional Data on the Real Line with the Wasserstein Metric

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