2 citations · 3 across the 13 of their papers we have counts for
6 papers · 1 filter
Tabular Numeric Stretch Transformation
Zihao Ye, Juyong Kim, Johnna Sundberg +2
Tabular data presents unique challenges for deep learning due to its heterogeneous nature, where numeric features exhibit diverse distributions, scales, and statistical properties.…
Context-Informed Ship Trajectory Prediction via Conditional Attention
Yuan Guan, Chandler Squires, Timothy Hu +1
Long-term ship trajectory prediction is a fundamental capability for maritime safety and autonomous navigation. While recent Transformer-based architectures have improved forecasti…
Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps
RuiKang OuYang, Hanlin Yu, Xinyue Ai +7
Recent progress in flow-based generative modeling has led to models that output high-quality samples while using only a small number of function evaluations. However, at present, t…
Catastrophic Compositional Generation: Why Vanilla Diffusion Models Fail to Extrapolate
Duncan Soiffer, Chandler Squires, Yuan Guan +2
The task of compositional generation involves using a conditional generative model, trained only on a subset of the possible conditions, to produce samples from compositionally-def…
Concept Modulation Models: A Unified Framework for Identifiability and Extrapolation
Soheun Yi, Yizhou Lu, Chandler Squires +1
Reliable generalization in conditional latent variable models requires understanding both identifiability and extrapolation: how observed variation across attributes determines lat…
A Unifying Framework for Unsupervised Concept Extraction
Chandler Squires, Pradeep Ravikumar
Techniques for concept extraction, such as sparse autoencoders and transcoders, aim to extract high-level symbolic concepts from low-level nonsymbolic representations. When these e…