Andrew Song — accepted AI-conference papers

2024

Multistain Pretraining for Slide Representation Learning in Pathology

Guillaume Jaume*, Anurag J Vaidya*, Andrew Zhang, Andrew Song, Richard J Chen, Sharifa Sahai +4

ECCV 2024poster

"Developing self-supervised learning (SSL) models that can learn universal and transferable representations of H&E gigapixel whole-slide images (WSIs) is becoming increasingly valuable in computational pathology. These models hold the potential to advance critical tasks such as few-shot classificati…

Cited by 11 Source ↗PDF ↗code ↗Scholar ↗

2020

Convolutional dictionary learning based auto-encoders for natural exponential-family distributions

Bahareh Tolooshams, Andrew Song, Simona Temereanca, Demba Ba

ICML 2020poster

We introduce a class of auto-encoder neural networks tailored to data from the natural exponential family (e.g., count data). The architectures are inspired by the problem of learning the filters in a convolutional generative model with sparsity constraints, often referred to as convolutional dictio…

Cited by 36 Source ↗PDF ↗code ↗Scholar ↗