Stat-Ml
On topological descriptors for graph products
FreDN: Spectral Disentanglement for Time Series Forecasting via Learnable Frequency Decomposition
Efficient Online Variational Estimation via Monte Carlo Sampling
Inference-Time Rethinking with Latent Thought Vectors for Math Reasoning
Operationalizing Stein's Method for Online Linear Optimization: CLT-Based Optimal Tradeoffs
Infinite-dimensional generative diffusions via Doob's h-transform
Which Graph Shift Operator? A Spectral Answer to an Empirical Question
Efficient Perplexity Bound and Ratio Matching in Discrete Diffusion Language Models
Position: Epistemic uncertainty estimation methods are fundamentally incomplete
A Kolmogorov-Arnold Neural Model for Cascading Extremes
Return Augmented Decision Transformer for Off-Dynamics Reinforcement Learning
Inheritance Between Feedforward and Convolutional Networks via Model Projection
High-dimensional censored MIDAS logistic regression for corporate survival forecasting
Adventures in Demand Analysis Using AI
Single-loop Algorithms for Stochastic Non-convex Optimization with Weakly-Convex Constraints
Dataset Distillation as Pushforward Optimal Quantization
Generative modelling with jump-diffusions
Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching
Continuous-time reinforcement learning: ellipticity enables model-free value function approximation
Sample Complexity of Causal Identification with Temporal Heterogeneity
Supercharging Simulation-Based Inference for Bayesian Optimal Experimental Design
Denoising Diffusions with Optimal Transport: Localization, Curvature, and Multi-Scale Complexity
