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Found 5 papers, 1 papers with code
In-Context Data Distillation with TabPFN
Foundation models have revolutionized tasks in computer vision and natural language processing.
Variational Inference with Continuously-Indexed Normalizing Flows
Continuously-indexed flows (CIFs) have recently achieved improvements over baseline normalizing flows on a variety of density estimation tasks.
Detecting anthropogenic cloud perturbations with deep learning
One of the most pressing questions in climate science is that of the effect of anthropogenic aerosol on the Earth's energy balance.
Localised Generative Flows
We argue that flow-based density models based on continuous bijections are limited in their ability to learn target distributions with complicated topologies, and propose localised generative flows (LGFs) to address this problem.
A Novel Representation of Neural Networks
However, the representation is non-standardized, and the gradient calculation methods are often performed using component-based approaches that break parameters down into scalar units, instead of considering the parameters as whole entities.
