EMaP: Explainable AI with Manifold-based Perturbations

Subjects: “…Artificial Intelligence & Machine Learning…”
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Autoencoders in Function Space

Subjects: “…Artificial Intelligence & Machine Learning…”
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Nonparametric Regression on Random Geometric Graphs Sampled from Submanifolds

Subjects: “…Artificial Intelligence & Machine Learning…”
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Distribution Estimation under the Infinity Norm

Subjects: “…Artificial Intelligence & Machine Learning…”
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Extending Temperature Scaling with Homogenizing Maps

Subjects: “…Artificial Intelligence & Machine Learning…”
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Density Estimation Using the Perceptron

Subjects: “…Artificial Intelligence & Machine Learning…”
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Simplex Constrained Sparse Optimization via Tail Screening

Subjects: “…Artificial Intelligence & Machine Learning…”
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Score-Based Diffusion Models in Function Space

Subjects: “…Artificial Intelligence & Machine Learning…”
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Regularized Rényi Divergence Minimization through Bregman Proximal Gradient Algorithms

Subjects: “…Artificial Intelligence & Machine Learning…”
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WEFE: A Python Library for Measuring and Mitigating Bias in Word Embeddings

Subjects: “…Artificial Intelligence & Machine Learning…”
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On Non-asymptotic Theory of Recurrent Neural Networks in Temporal Point Processes

Subjects: “…Artificial Intelligence & Machine Learning…”
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Classification in the high dimensional Anisotropic mixture framework: A new take on Robust Interpolation

Subjects: “…Artificial Intelligence & Machine Learning…”
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Universal Online Convex Optimization Meets Second-order Bounds

Subjects: “…Artificial Intelligence & Machine Learning…”
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Randomization Can Reduce Both Bias and Variance: A Case Study in Random Forests

Subjects: “…Artificial Intelligence & Machine Learning…”
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Losing Momentum in Continuous-time Stochastic Optimisation

Subjects: “…Artificial Intelligence & Machine Learning…”
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Latent Process Models for Functional Network Data

Subjects: “…Artificial Intelligence & Machine Learning…”
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Fine-grained Analysis and Faster Algorithms for Iteratively Solving Linear Systems

Subjects: “…Artificial Intelligence & Machine Learning…”
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Deep Generative Models: Complexity, Dimensionality, and Approximation

Subjects: “…Artificial Intelligence & Machine Learning…”
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ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation

Subjects: “…Artificial Intelligence & Machine Learning…”
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Conditional Wasserstein Distances with Applications in Bayesian OT Flow Matching

Subjects: “…Artificial Intelligence & Machine Learning…”
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