The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers. - Alex X. Lu; Amy X. Lu; Wiebke Schormann; Marzyeh Ghassemi; David W. Andrews; Alan M. Moses (NeurIPS, 2019)

YeastSpotter: accurate and parameter-free web segmentation for microscopy images of yeast cells. - Alex X. Lu; Taraneh Zarin; Ian Shenyen Hsu; Alan M. Moses (Bioinform., 2019)

The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers. - Alex X. Lu; Amy X. Lu; Wiebke Schormann; David W. Andrews; Alan M. Moses (CoRR, 2019)

Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting. - Alex X. Lu; Oren Z. Kraus; Sam Cooper; Alan M. Moses (PLoS Comput. Biol., 2019)

Improved Conditional Flow Models for Molecule to Image Synthesis. - Karren D. Yang; Samuel Goldman; Wengong Jin; Alex Lu 002; Regina Barzilay; Tommi S. Jaakkola; Caroline Uhler (CoRR, 2020)

Evolution Is All You Need: Phylogenetic Augmentation for Contrastive Learning. - Amy X. Lu; Alex X. Lu; Alan M. Moses (CoRR, 2020)

Mol2Image: Improved Conditional Flow Models for Molecule to Image Synthesis. - Karren D. Yang; Samuel Goldman; Wengong Jin; Alex X. Lu; Regina Barzilay; Tommi S. Jaakkola; Caroline Uhler (CVPR, 2021)

Random Embeddings and Linear Regression can Predict Protein Function. - Tianyu Lu; Alex X. Lu; Alan M. Moses (CoRR, 2021)

CytoImageNet: A large-scale pretraining dataset for bioimage transfer learning. - Stanley Bryan Z. Hua; Alex X. Lu; Alan M. Moses (CoRR, 2021)

Unsupervised machine learning for hypothesis discovery and representation learning in biological image and sequence analysis. - Alex Lu 002 (2021)

Protein structure generation via folding diffusion. - Kevin E. Wu; Kevin K. Yang; Rianne van den Berg; James Y. Zou; Alex X. Lu; Ava P. Amini (CoRR, 2022)

Discovering molecular features of intrinsically disordered regions by using evolution for contrastive learning. - Alex X. Lu; Amy X. Lu; Iva Pritisanac; Taraneh Zarin; Julie D. Forman-Kay; Alan M. Moses (PLoS Comput. Biol., 2022)

Domain adaptation using optimal transport for invariant learning using histopathology datasets. - Kianoush Falahkheirkhah; Alex Xijie Lu; David Alvarez-Melis; Grace Huynh (MIDL, 2023)

ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition. - Aashaka Desai; Lauren Berger; Fyodor Minakov; Nessa Milano; Chinmay Singh; Kriston Pumphrey; Richard E. Ladner; Hal Daumé III; Alex X. Lu; Naomi Caselli; Danielle Bragg (NeurIPS, 2023)

ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition. - Aashaka Desai; Lauren Berger; Fyodor O. Minakov; Vanessa Milan; Chinmay Singh; Kriston Pumphrey; Richard E. Ladner; Hal Daumé III; Alex X. Lu; Naomi Caselli; Danielle Bragg (CoRR, 2023)

ASL STEM Wiki: Dataset and Benchmark for Interpreting STEM Articles. - Kayo Yin; Chinmay Singh; Fyodor Minakov; Vanessa Milan; Hal Daumé III; Cyril Zhang; Alex Lu 002; Danielle Bragg (EMNLP, 2024)

Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models. - Francesca-Zhoufan Li; Ava P. Amini; Yisong Yue; Kevin K. Yang; Alex Xijie Lu (ICML, 2024)

Systemic Biases in Sign Language AI Research: A Deaf-Led Call to Reevaluate Research Agendas. - Aashaka Desai; Maartje de Meulder; Julie A. Hochgesang; Annemarie Kocab; Alex X. Lu (CoRR, 2024)

Exploring Reduced Feature Sets for American Sign Language Dictionaries. - Ben Kosa; Aashaka Desai; Alex X. Lu; Richard E. Ladner; Danielle Bragg (CHI, 2025)

Causal integration of chemical structures improves representations of microscopy images for morphological profiling. - Yemin Yu; Neil A. Tenenholtz; Lester Mackey; Ying Wei; David Alvarez-Melis; Ava P. Amini; Alex X. Lu (CoRR, 2025)