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

[abs][Download PDF]

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

[abs][Download PDF]

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

[abs][Download PDF]

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

[abs][Download PDF]

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

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

[abs][Download PDF]

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

[abs][Download PDF]

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

[abs][Download PDF]

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

[abs][Download PDF]

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

[abs][Download PDF]

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

[abs][Download PDF]

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

[abs][Download PDF]