2 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
SurrogateSHAP: Training-Free Contributor Attribution for Text-to-Image (T2I) Models
Mingyu Lu, Soham Gadgil, Chris Lin +2
As Text-to-Image (T2I) diffusion models are increasingly used in real-world creative workflows, a principled framework for valuing contributors who provide a collection of data is…
CellCLIP -- Learning Perturbation Effects in Cell Painting via Text-Guided Contrastive Learning
Mingyu Lu, Ethan Weinberger, Chanwoo Kim +1
High-content screening (HCS) assays based on high-throughput microscopy techniques such as Cell Painting have enabled the interrogation of cells' morphological responses to perturb…
An Efficient Framework for Crediting Data Contributors of Diffusion Models
Chris Lin, Mingyu Lu, Chanwoo Kim +1
As diffusion models are deployed in real-world settings, and their performance is driven by training data, appraising the contribution of data contributors is crucial to creating i…
A Deep Bayesian Bandits Approach for Anticancer Therapy: Exploration via Functional Prior
Mingyu Lu, Yifang Chen, Su-In Lee
Learning personalized cancer treatment with machine learning holds great promise to improve cancer patients' chance of survival. Despite recent advances in machine learning and pre…