All articles
arxiv arXiv cs.LG · 10h ago

STAITUS: Disentangling Appearance and Pose for Video Object Tracking

The article introduces STAITUS, a unified framework for unsupervised video object tracking that addresses the limitations of existing slot-based representations by explicitly disentangling appearance from geometric pose. By applying temporal alignment only in appearance space and enforcing spatial separation within frames, the method prevents slots from locking onto static backgrounds during motion.

arxiv arXiv cs.LG · 11h ago

Time Series Classification through Diffeomorphic Time Warping (DiffTW)

The article introduces Diffeomorphic Time Warping (DiffTW), a theoretical framework for time series classification that learns mappings between real-valued functions to overcome the discrete point matching limitations of Dynamic Time Warping (DTW). DiffTW approximates diffeomorphic transformations using the method of characteristics to solve linear transport equations, providing a theoretically grounded dissimilarity measure.

arxiv arXiv cs.LG · 11h ago

Sublinearly Structured Deep Neural Networks Achieve Feature Learning Consistency for Compositional Functions

This study establishes feature-learning consistency guarantees for a broad subclass of deep neural networks characterized by sublinear growth in input/output dimensions and hidden neurons relative to sample size. The authors prove that these architectures achieve universal approximation for hierarchically compositional functions, even within the conventional over-parameterized regime where parameters exceed training samples.