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  1. Toolbox for Multimodal Learn (scikit-multimodallearn)

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  2. Analytically Tractable Hidden-States Inference in Bayesian Neural Networks

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

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

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  5. Cascaded Diffusion Models for High Fidelity Image Generation

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

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  7. Optimal Transport for Stationary Markov Chains via Policy Iteration

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  8. PAC Guarantees and Effective Algorithms for Detecting Novel Categories

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  9. Sampling Permutations for Shapley Value Estimation

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

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  11. The correlation-assisted missing data estimator

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  12. Structure-adaptive Manifold Estimation

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

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  14. Score Matched Neural Exponential Families for Likelihood-Free Inference

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

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  16. Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization

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  17. Optimality and Stability in Non-Convex Smooth Games

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  18. SODEN: A Scalable Continuous-Time Survival Model through Ordinary Differential Equation Networks

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  19. Model Averaging Is Asymptotically Better Than Model Selection For Prediction

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