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math.PR2026
Approximating Measures on Function Spaces: Transport and Truncation
Ricardo Baptista, Bamdad Hosseini, Alexander W. Hsu
Measures on function spaces arise throughout Bayesian inverse problems and generative modeling, often with low-dimensional structure relative to a tractable reference measure. We i…
cs.LG2026
Training-Free Universal Approximation by Prompting Random Transformers
Alexander Hsu, Rongjie Lai
How expressive is prompting a transformer? Answering this question is important for separating the roles of prompting, architecture, and pretraining in transformer models, and for…
cs.LG2026
Understanding In-Context Learning for Nonlinear Regression with Transformers: Attention as Featurizer
Alexander Hsu, Zhaiming Shen, Wenjing Liao +1
Pre-trained transformers are able to learn from examples provided as part of the prompt without any weight updates, a remarkable ability known as in-context learning (ICL). Despite…