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Kuramoto Orientation Diffusion Models
Yue Song, T. Anderson Keller, Sevan Brodjian +4
Orientation-rich images, such as fingerprints and textures, often exhibit coherent angular directional patterns that are challenging to model using standard generative approaches b…
Flow Equivariant Recurrent Neural Networks
T. Anderson Keller
Data arrives at our senses as a continuous stream, smoothly transforming from one instant to the next. These smooth transformations can be viewed as continuous symmetries of the en…
Langevin Flows for Modeling Neural Latent Dynamics
Yue Song, T. Anderson Keller, Yisong Yue +2
Neural populations exhibit latent dynamical structures that drive time-evolving spiking activities, motivating the search for models that capture both intrinsic network dynamics an…
Unsupervised Representation Learning from Sparse Transformation Analysis
Yue Song, Thomas Anderson Keller, Yisong Yue +2
There is a vast literature on representation learning based on principles such as coding efficiency, statistical independence, causality, controllability, or symmetry. In this pape…