2 citations · 2 across the 3 of their papers we have counts for
3 papers
Unlearning Information Bottleneck: Machine Unlearning of Systematic Patterns and Biases
Ling Han, Hao Huang, Dustin Scheinost +2
Effective adaptation to distribution shifts in training data is pivotal for sustaining robustness in neural networks, especially when removing specific biases or outdated informati…
Enhancement attacks in biomedical machine learning
Matthew Rosenblatt, Javid Dadashkarimi, Dustin Scheinost
The prevalence of machine learning in biomedical research is rapidly growing, yet the trustworthiness of such research is often overlooked. While some previous works have investiga…
Data-driven mapping between functional connectomes using optimal transport
Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost
Functional connectomes derived from functional magnetic resonance imaging have long been used to understand the functional organization of the brain. Nevertheless, a connectome is…