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Volume 200: Machine Learning in Computational Biology, 21-22 November 2022, Online

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Editors: David A Knowles, Sara Mostafavi, Su-In Lee

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CVQVAE: A representation learning based method for multi-omics single cell data integration

Tianyu Liu, Grant Greenberg, Ilan Shomorony; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:1-15

Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI

Ethan Weinberger, Romain Lopez, Jan-Christian Huetter, Aviv Regev; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:16-32

Ensembling improves stability and power of feature selection for deep learning models

Prashnna K. Gyawali, Xiaoxia Liu, James Zou, Zihuai He; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:33-45

Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMs

Vidhi Lalchand, Aditya Ravuri, Emma Dann, Natsuhiko Kumasaka, Dinithi Sumanaweera, Rik G. H. Lindeboom, Shaista Madad, Sarah Teichmann, Neil D. Lawrence; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:46-60

A generative recommender system with GMM prior for cancer drug generation and sensitivity prediction

Krzysztof Koras, Marcin MoĹžejko, Paulina Szymczak, Adam Izdebski, Eike Staub, Ewa Szczurek; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:61-73

Incorporating knowledge of plates in batch normalization improves generalization of deep learning for microscopy images

Alexander Lin, Alex Lu; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:74-93

Energy-based Modelling for Single-cell Data Annotation

Tianyi Liu, Philip Fradkin, Lazar Atanackovic, Leo J Lee; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:94-109

Predicting Immune Escape with Pretrained Protein Language Model Embeddings

Kyle Swanson, Howard Chang, James Zou; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:110-130

Selecting deep neural networks that yield consistent attribution-based interpretations for genomics

Antonio Majdandzic, Chandana Rajesh, Ziqi Tang, Shushan Toneyan, Ethan L. Labelson, Rohit K. Tripathy, Peter K. Koo; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:131-149

Language-Informed Basecalling Architecture for Nanopore Direct RNA Sequencing

Alexandra Sneddon, Pablo Acera Mateos, Nikolay Shirokikh, Eduardo Eyras; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:150-165

Forecasting labels under distribution-shift for machine-guided sequence design

Lauren B Wheelock, Stephen Malina, Jeffrey Gerold, Sam Sinai; Proceedings of the 17th Machine Learning in Computational Biology meeting, PMLR 200:166-180

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