22 citations · 34 across the 8 of their papers we have counts for
5 papers · 1 filter
FLUX: Geometry-Aware Longitudinal Flow Matching with Mixture of Experts
Josue Ortega Caro, Yongxu Zhang, Hannah M Batchelor +3
Many biological systems evolve through continuous local dynamics while switching between latent regimes defined by learning, stimulus context, internal state, or developmental stag…
Continuous Spatiotemporal Transformers
Antonio H. de O. Fonseca, Emanuele Zappala, Josue Ortega Caro +1
Modeling spatiotemporal dynamical systems is a fundamental challenge in machine learning. Transformer models have been very successful in NLP and computer vision where they provide…
FIMP: Foundation Model-Informed Message Passing for Graph Neural Networks
Syed Asad Rizvi, Nazreen Pallikkavaliyaveetil, David Zhang +15
Foundation models have achieved remarkable success across many domains, relying on pretraining over vast amounts of data. Graph-structured data often lacks the same scale as unstru…
Neural Integral Equations
Emanuele Zappala, Antonio Henrique de Oliveira Fonseca, Josue Ortega Caro +4
Nonlinear operators with long distance spatiotemporal dependencies are fundamental in modeling complex systems across sciences, yet learning these nonlocal operators remains challe…
Shallow Univariate ReLu Networks as Splines: Initialization, Loss Surface, Hessian, & Gradient Flow Dynamics
Justin Sahs, Ryan Pyle, Aneel Damaraju +4
Understanding the learning dynamics and inductive bias of neural networks (NNs) is hindered by the opacity of the relationship between NN parameters and the function represented. W…