Nature

Realistic simulation of virtual multi-scale, multi-modal patient trajectories using Bayesian networks and sparse auto-encoders

Translational research of many disease areas requires a longitudinal understanding of disease development and progression across all biologically relevant scales. Several corresponding studies are now ...
Harvard Business School

Temporal Sparse Autoencoders: Leveraging the Sequential Nature of Language for Interpretability

Bhalla, Usha, Alex Oesterling, Claudio Mayrink Verdun, Himabindu Lakkaraju, and Flavio Calmon. "Temporal Sparse Autoencoders: Leveraging the Sequential Nature of Language for Interpretability." ...
The Scientist

Researchers Decode How Protein Language Models Think, Making AI More Transparent

For large language models (LLMs) like ChatGPT, accuracy often means complexity. To be able to make good predictions, ChatGPT must deeply understand the concepts and features that are associated with ...
Nature

Breath analysis based early gastric cancer classification from deep stacked sparse autoencoder neural network

Deep learning is an emerging tool, which is regularly used for disease diagnosis in the medical field. A new research direction has been developed for the detection of early-stage gastric cancer. The ...
Harvard Business School

Evaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders

Jiaxun Li, Aaron, Suraj Srinivas, Usha Bhalla, and Himabindu Lakkaraju. "Evaluating Adversarial Robustness of Concept Representations in Sparse Autoencoders." Proceedings of the Conference of the ...