Deep Learning Automates the Quantitative Analysis of Individual Cells in Live-Cell Imaging Experiments. - David A. Van Valen; Takamasa Kudo; Keara M. Lane; Derek N. Macklin; Nicolas T. Quach; Mialy M. DeFelice; Inbal Maayan; Yu Tanouchi; Euan A. Ashley; Markus W. Covert (PLoS Comput. Biol., 2016)

A Supervised Contrastive Framework for Learning Disentangled Representations of Cellular Perturbation Data. - Xinming Tu; Jan-Christian Hütter; Zitong Jerry Wang; Takamasa Kudo; Aviv Regev; Romain Lopez (MLCB, 2023)

Sequential Optimal Experimental Design of Perturbation Screens Guided by Multi-modal Priors. - Kexin Huang; Romain Lopez; Jan-Christian Hütter; Takamasa Kudo; Antonio Rios; Aviv Regev (RECOMB, 2024)

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)