David Richmond

According to our database, David Richmond authored at least 19 papers between 2017 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

AssayBench: An Assay-Level Virtual Cell Benchmark for LLMs and Agents.

Edward De Brouwer, Carl Edwards, Alexander Wu, Jenna Collier, Graham Heimberg, Xiner Li, Meena Subramaniam, Ehsan Hajiramezanali, David Richmond, Jan-Christian Hütter, Sara Mostafavi, Gabriele Scalia

CoRR, May, 2026

Incorporating contextual information into KGWAS for interpretable GWAS discovery.

Cheng Jiang, Brady Ryan, Megan Crow, Kipper Fletez-Brant, Kashish Doshi, Sandra Melo Carlos, Kexin Huang, Burkhard Hoeckendorf, Heming Yao, David Richmond

CoRR, March, 2026

2025

Sparse Mixture-of-Experts for Multi-Channel Imaging: Are All Channel Interactions Required?

Sukwon Yun, Heming Yao, Burkhard Hoeckendorf, David Richmond, Aviv Regev, Russell Littman

CoRR, November, 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, September, 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, Aviv Regev, Romain Lopez

CoRR, February, 2025

Contextualizing biological perturbation experiments through language.

Menghua Wu, Russell Littman, Jacob Levine, Lin Qiu, Tommaso Biancalani, David Richmond, Jan-Christian Huetter

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Weakly Supervised Set-Consistency Learning Improves Morphological Profiling of Single-Cell Images.

Heming Yao, Phil Hanslovsky, Jan-Christian Huetter, Burkhard Hoeckendorf, David Richmond

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Gene-Level Representation Learning via Interventional Style Transfer in Optical Pooled Screening.

Mahtab Bigverdi, Burkhard Höckendorf, Heming Yao, Phil Hanslovsky, Romain Lopez, David Richmond

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Unsupervised Segmentation of Colonoscopy Images.

Heming Yao, Jérôme Lüscher, Benjamín Gutiérrez-Becker, Josep Arús-Pous, Tommaso Biancalani, Amelie Bigorgne, David Richmond

CoRR, 2023

2021

Confidence-Guided Learning For Breast Density Classification.

Sun Young Park, Dustin Sargent, David Richmond

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Pneumoperitoneum Detection In Chest X-Ray By A Deep Learning Ensemble With Model Explainability.

María V. Sainz de Cea, David Gruen, David Richmond

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 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

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Reading Mammography with Multiple Prior Exams.

Chao Song, Maria V. Sainz de Cea, David Richmond

Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

2019

Breast density follow-up decision support system using deep convolutional models.

Sun Young Park, Dustin Sargent, David Richmond

Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019

2018

Pre-training on Grayscale ImageNet Improves Medical Image Classification.

Yiting Xie, David Richmond

Proceedings of the Computer Vision - ECCV 2018 Workshops, 2018

2017

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