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- Robust Log-Contrast Regression for High-Dimensional Compositional Microbiome Data with Outliers
- Error analysis and optimal sample allocation for randomized unbiased estimation: the single term estimator
- PDE-Based Bounds on Optimal Exponents in Active Simple Hypothesis Testing
- Axiomatic Learning and Probabilistic Structures with first applications to variants of Arithmetic Machine Learning and beyond
- Wasserstein approximation of measures via orthogonal frames: statistical and computational complexities
- Second-order Sinkhorn Geometry and √n-Inference
- A Simple Presentation of Robust Membership Inference Attacks
- Bias Correction and Inference for Panel Quantile Regression
- Fixed-Horizon Error Rates for Array-RQMC Metropolis-Hastings
- Demand Estimation with Unobserved Stockout Substitution: Exact Likelihood Maximization
- Hilbert-Scale Stability of Posterior Diffusion Priors for Ill-Posed Signal Recovery
- Reconstructing constant point heat sources from few temperature sensors: sparse selection and spatial resolution
- Asymptotics and finite sample bounds for prediction and smoothing in Wright-Fisher hidden Markov models
- Momentum in large-batch training: Polyak enlarges the critical batch size, Nesterov improves data efficiency
- A general-purpose multi-path stacked coupling for stochastic reaction networks
- Kähler landscapes for complex neural network descents and guarantees including a search and destroy of the Calabi-Yau manifold
- Phases of Muon: When Muon Eclipses SignSGD
- An Input Skip Can Reparameterize a VAE Without Improving the Generator
- An end-to-end framework for uncertainty-aware validation of generative models
- Physics-Guided Flow Matching: A Generative AI Framework for Global Total Electron Content Forecasting
- Generative Refinement Learning for Temporal Interpolation in Scientific Machine Learning
- When Scatter Plots Hide the Data: Diagnosing Ties and Choosing the Right Display in R
- Advantage of Sample Complexity in Quantum PAC Learning Requires Inverse Access to State-Preparation Unitaries
- Modeling Dependence Structures in Astronomical Multi-Band Time Series Data via Multi-Output Gaussian Processes
- An Asymptotic Theory of Chain-of-Thought in In-Context Learning