DeadNet: Identifying Phototoxicity from Label-free Microscopy Images of Cells using Deep ConvNets. - David Richmond; Anna Payne-Tobin Jost; Talley Lambert; Jennifer Waters; Hunter Elliott (CoRR, 2017)

Pre-training on Grayscale ImageNet Improves Medical Image Classification. - Yiting Xie; David Richmond (ECCV Workshops (6), 2018)

Breast density follow-up decision support system using deep convolutional models. - Sun Young Park; Dustin Sargent; David Richmond (Computer-Aided Diagnosis, 2019)

Reading Mammography with Multiple Prior Exams. - Chao Song; Maria V. Sainz de Cea; David Richmond (ISBI, 2020)

Deep Learning Based Detection of Acute Aortic Syndrome in Contrast CT Images. - Manikanta Srikar Yellapragada; Yiting Xie; Benedikt Graf; David Richmond; Arun Krishnan; Arkadiusz Sitek (ISBI, 2020)

Multi-task Learning for Detection and Classification of Cancer in Screening Mammography. - Maria V. Sainz de Cea; Karl Diedrich; Ran Bakalo; Lior Ness; David Richmond (MICCAI (6), 2020)

Multi-site Evaluation of a Study-Level Classifier for Mammography Using Deep Learning. - Dustin Sargent; Sun Young Park; Amod Jog; Aly A. Mohamed; David Richmond (MICCAI (6), 2020)

Pneumoperitoneum Detection In Chest X-Ray By A Deep Learning Ensemble With Model Explainability. - María V. Sainz de Cea; David Gruen; David Richmond (ISBI, 2021)

Confidence-Guided Learning For Breast Density Classification. - Sun Young Park; Dustin Sargent; David Richmond (ISBI, 2021)

Unsupervised Segmentation of Colonoscopy Images. - Heming Yao; Jérôme Lüscher; Benjamín Gutiérrez-Becker; Josep Arús-Pous; Tommaso Biancalani; Amelie Bigorgne; David Richmond (CoRR, 2023)

Gene-Level Representation Learning via Interventional Style Transfer in Optical Pooled Screening. - Mahtab Bigverdi; Burkhard Höckendorf; Heming Yao; Phil Hanslovsky; Romain Lopez; David Richmond (CVPR Workshops, 2024)

Weakly Supervised Set-Consistency Learning Improves Morphological Profiling of Single-Cell Images. - Heming Yao; Phil Hanslovsky; Jan-Christian Huetter; Burkhard Hoeckendorf; David Richmond (CVPR Workshops, 2024)

Learning Identifiable Factorized Causal Representations of Cellular Responses. - Haiyi Mao; Romain Lopez; Kai Liu; Jan-Christian Huetter; David Richmond; Panayiotis V. Benos; Lin Qiu (NeurIPS, 2024)

Contextualizing biological perturbation experiments through language. - Menghua Wu; Russell Littman; Jacob Levine; Lin Qiu; Tommaso Biancalani; David Richmond; Jan-Christian Huetter (ICLR, 2025)

Supervised Contrastive Block Disentanglement. - Taro Makino; Ji Won Park; Natasa Tagasovska; Takamasa Kudo; Paula Coelho; Jan-Christian Huetter; Heming Yao; Burkhard Hoeckendorf; Ana Carolina Leote; Stephen Ra; David Richmond; Kyunghyun Cho; et al. (CoRR, 2025)

HypoGeneAgent: A Hypothesis Language Agent for Gene-Set Cluster Resolution Selection Using Perturb-seq Datasets. - Ying Yuan; Xing-Yue Monica Ge; Aaron Archer Waterman; Tommaso Biancalani; David Richmond; Yogesh Pandit; Avtar Singh; Russell Littman; Jin Liu; Jan-Christian Huetter; Vladimir Ermakov (CoRR, 2025)