1,205 records
- A Fourier perspective on the learning dynamics of neural networks: from sample complexities to mechanistic insights
- Diffusion-Based Stochastic Operator Networks for Uncertainty Quantification in Stochastic Partial Differential Equations
- Sample-efficient inductive matrix completion with noise and inexact side-information
- $α$-TCAV: A Unified Framework for Testing with Concept Activation Vectors
- Testing properties of trees in graphical models with covariance queries
- Dimension-Uniform Discretization Analysis of Preconditioned Annealed Langevin Dynamics for Multimodal Gaussian Mixtures
- Adaptive Long-Run Variance Thresholding for Sparse Covariance Estimation in High-Dimensional Time Series
- A Bayesian Longitudinal Spatial Normative Model for Individualized Brain Deviation Mapping
- Scaling Laws from Sequential Feature Recovery: A Solvable Hierarchical Model
- Parametrically Adaptive Transition Polynomial: a Signed-Parity Continuous-alpha Extension of Kunchenko Stochastic Polynomials
- Differentially private inference framework for Riemannian manifold data
- Average Gradient Outer Product in kernel regression provably recovers the central subspace for multi-index models
- Harnessing Unimodality in Semiparametric Contextual Pricing via Oracle Price Map Learning
- State-of-art minibatches via novel DPP kernels: discretization, wavelets, and rough objectives
- The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
- Learning Perturbations to Extrapolate Your LLM
- On the Limits of Latent Reuse in Diffusion Models
- Structural identifiability of partially-observed stochastic processes: from single-particle trajectories to total particle density data
- What is Learnable in Valiant's Theory of the Learnable?
- Predictive Inference via Kernel Density Estimates
- Posterior Contraction Rates for Sparse Kolmogorov-Arnold Networks in Anisotropic Besov Spaces
- Model-based Bootstrap of Controlled Markov Chains
- A Unified Framework for Critical Scaling of Inverse Temperature in Self-Attention
- A Statistical Framework for Learning Preferences from the Past
- Characterizing the Generalization Error of Random Feature Regression with Arbitrary Data-Augmentation
- Affine Tracing: A New Paradigm for Probabilistic Linear Solvers
- Price of Quality: Sufficient Conditions for Sparse Recovery using Mixed-Quality Data
- Uniform Scaling Limits in AdamW-Trained Transformers
- Quantitative Local Convergence of Mean-Field Stein Variational Gradient Flow
- Proximal Path-Specific Inference
- Learning stochastic multiscale models through normalizing flows
- Core-Halo Decomposition: Decentralizing Large-Scale Fixed-Point Problems
- Measuring and Decomposing Mode Separation via the Canonical Diffusion
- Tight Generalization Bounds for Noiseless Inverse Optimization
- Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity
- TopoFisher: Learning Topological Summary Statistics by Maximizing Fisher Information
- Expectation-Maximization as a Spectrally Governed Relaxation Flow
- Parametric ROC Analysis and Optimal Cutoff Selection under Scale Mixtures of Skew-Normal Distributions: A Decision-Theoretic Framework with Asymptotic Inference
- Cellwise and Casewise Robust Multivariate Regression with Inference
- A Note on Non-Negative $L_1$-Approximating Polynomials
- Sinkhorn Treatment Effects: A Causal Optimal Transport Measure
- Sliced Inner Product Gromov-Wasserstein Distances
- Variational Smoothing and Inference for SDEs from Sparse Data with Dynamic Neural Flows
- A Stein Characterization-type Omnibus Tests for the Discrete Pareto Distribution
- Ratio-based Loss Functions
- CITE: Anytime-Valid Statistical Inference in LLM Self-Consistency
- Expressivity of Bi-Lipschitz Normalizing Flows: A Score-Based Diffusion Perspective
- Risk-Controlled Post-Processing of Decision Policies
- How Does Attention Help? Insights from Random Matrices on Signal Recovery from Sequence Models
- One Operator for Many Densities: Amortized Approximation of Conditioning by Neural Operators