The Lair: a resource for exploratory analysis of published RNA-Seq data. - Harold Pimentel; Pascal Sturmfels; Nicolas Bray; Páll Melsted; Lior Pachter (BMC Bioinform., 2016)

A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images. - Pascal Sturmfels; Saige Rutherford; Mike Angstadt; Mark Peterson; Chandra Sekhar Sripada; Jenna Wiens (MLHC, 2018)

Learning Explainable Models Using Attribution Priors. - Gabriel G. Erion; Joseph D. Janizek; Pascal Sturmfels; Scott M. Lundberg; Su-In Lee (CoRR, 2019)

Select and permute: An improved online framework for scheduling to minimize weighted completion time. - Samir Khuller; Jingling Li; Pascal Sturmfels; Kevin Sun 001; Prayaag Venkat (Theor. Comput. Sci., 2019)

Profile Prediction: An Alignment-Based Pre-Training Task for Protein Sequence Models. - Pascal Sturmfels; Jesse Vig; Ali Madani; Nazneen Fatema Rajani (CoRR, 2020)

Explaining Explanations: Axiomatic Feature Interactions for Deep Networks. - Joseph D. Janizek; Pascal Sturmfels; Su-In Lee (J. Mach. Learn. Res., 2021)

Improving performance of deep learning models with axiomatic attribution priors and expected gradients. - Gabriel G. Erion; Joseph D. Janizek; Pascal Sturmfels; Scott M. Lundberg; Su-In Lee (Nat. Mach. Intell., 2021)

FoggySight: A Scheme for Facial Lookup Privacy. - Ivan Evtimov; Pascal Sturmfels; Tadayoshi Kohno (Proc. Priv. Enhancing Technol., 2021)

Automated Brain Masking of Fetal Functional MRI with Open Data. - Saige Rutherford; Pascal Sturmfels; Mike Angstadt; Jasmine L. Hect; Jenna Wiens; Marion I. van den Heuvel; Dustin Scheinost; Chandra Sekhar Sripada; Moriah E. Thomason (Neuroinformatics, 2022)

Explainable Machine Learning and Applications in Protein-Ligand Complex Structure Prediction - Pascal Sturmfels (2024)