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Publication search results
found 37 matches
- 2023
- Ethar Alzaid, Muhammad Dawood, Fayyaz Minhas:
A Transductive Approach to Survival Ranking for Cancer Risk Stratification. MLCB 2023: 101-109 - Ayesha Bajwa, Ruchir Rastogi, Pooja Kathail, Richard W. Shuai, Nilah Ioannidis:
Characterizing uncertainty in predictions of genomic sequence-to-activity models. MLCB 2023: 279-297 - Juneki Hong, Dezhong Deng, David A. Hendrix:
Improving transformer secondary structure predictions with secondary structure "fixing" task. MLCB 2023: 267-278 - Keren Isaev, David A. Knowles:
Investigating RNA splicing as a source of cellular diversity using a binomial mixture model. MLCB 2023: 163-175 - Neda Shokraneh Kenari, Megan Andrews, Max W. Libbrecht:
Model-based imputation enables improved resolution for identifying differential chromatin contacts in single-cell Hi-C data. MLCB 2023: 176-193 - Renming Liu, Arjun Krishnan:
Open Biomedical Network Benchmark: A Python Toolkit for Benchmarking Datasets with Biomedical Networks. MLCB 2023: 23-59 - Arushi G. K. Majha, Ian Stott, Andreas Bender:
On Modelability and Generalizability: Are Machine Learning Models for Drug Synergy Exploiting Artefacts and Biases in Available Data? MLCB 2023: 123-134 - Kaspar Märtens, Christopher Yau:
Disentangling shared and private latent factors in multimodal Variational Autoencoders. MLCB 2023: 60-75 - Andrea Nathansen, Kevin Klein, Bernhard Y. Renard, Melania Nowicka, Jakub M. Bartoszewicz:
Evaluating Tuning Strategies for Sequence Generation with Protein Language Models. MLCB 2023: 76-89 - Eyes S. Robson, Nilah Ioannidis:
GUANinE v1.0: Benchmark Datasets for Genomic AI Sequence-to-Function Models. MLCB 2023: 250-266 - Zachary S. Sims, Young Hwan Chang:
A Masked Image Modeling Approach to CyCIF Panel Reduction and Marker Imputation. MLCB 2023: 1-9 - Antoine Szatkownik, Cyril Furtlehner, Guillaume Charpiat, Burak Yelmen, Flora Jay:
Towards creating longer genetic sequences with GANs: Generation in principal component space. MLCB 2023: 110-122 - Xinming Tu, Jan-Christian Hütter, Zitong Jerry Wang, Takamasa Kudo, Aviv Regev, Romain Lopez:
A Supervised Contrastive Framework for Learning Disentangled Representations of Cellular Perturbation Data. MLCB 2023: 90-100 - Gian Marco Visani, William Galvin, Michael N. Pun, Armita Nourmohammad:
H-Packer: Holographic Rotationally Equivariant Convolutional Neural Network for Protein Side-Chain Packing. MLCB 2023: 230-249 - You Wu, Omid Bazgir, Yongju Lee, Tommaso Biancalani, James Lu, Ehsan Hajiramezanali:
Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction. MLCB 2023: 10-22 - Kevin E. Wu, Kathryn Yost, Bence Daniel, Julia A. Belk, Yu Xia, Takeshi Egawa, Ansuman Satpathy, Howard Chang, James Zou:
TCR-BERT: learning the grammar of T-cell receptors for flexible antigen-binding analyses. MLCB 2023: 194-229 - Jennifer Yu, Zhenqin Wu, Aaron T. Mayer, Alexandro Trevino, James Zou:
A Multi-Granularity Approach to Similarity Search in Multiplexed Immunofluorescence Images. MLCB 2023: 135-147 - Chenwei Zhang, Jordan Lovrod, Boyan Beronov, Khanh Dao Duc, Anne Condon:
ViDa: Visualizing DNA hybridization trajectories with biophysics-informed deep graph embeddings. MLCB 2023: 148-162 - David A. Knowles, Sara Mostafavi:
Machine Learning in Computational Biology, November 30 - December 1, 2023, Seattle, WA, USA. Proceedings of Machine Learning Research 240, PMLR 2023 [contents] - 2022
- Prashnna K. Gyawali, Xiaoxia Liu, James Zou, Zihuai He:
Ensembling improves stability and power of feature selection for deep learning models. MLCB 2022: 33-45 - Krzysztof Koras, Marcin Mozejko, Paulina Szymczak, Adam Izdebski, Eike Staub, Ewa Szczurek:
A generative recommender system with GMM prior for cancer drug generation and sensitivity prediction. MLCB 2022: 61-73 - Vidhi Lalchand, Aditya Ravuri, Emma Dann, Natsuhiko Kumasaka, Dinithi Sumanaweera, Rik G. H. Lindeboom, Shaista Madad, Sarah A. Teichmann, Neil D. Lawrence:
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMs. MLCB 2022: 46-60 - Alexander Lin, Alex Lu:
Incorporating knowledge of plates in batch normalization improves generalization of deep learning for microscopy images. MLCB 2022: 74-93 - Tianyi Liu, Philip Fradkin, Lazar Atanackovic, Leo J. Lee:
Energy-based Modelling for Single-cell Data Annotation. MLCB 2022: 94-109 - Tianyu Liu, Grant Greenberg, Ilan Shomorony:
CVQVAE: A representation learning based method for multi-omics single cell data integration. MLCB 2022: 1-15 - Antonio Majdandzic, Chandana Rajesh, Ziqi Tang, Shushan Toneyan, Ethan L. Labelson, Rohit K. Tripathy, Peter K. Koo:
Selecting deep neural networks that yield consistent attribution-based interpretations for genomics. MLCB 2022: 131-149 - Alexandra Sneddon, Pablo Acera Mateos, Nikolay Shirokikh, Eduardo Eyras:
Language-Informed Basecalling Architecture for Nanopore Direct RNA Sequencing. MLCB 2022: 150-165 - Kyle Swanson, Howard Chang, James Zou:
Predicting Immune Escape with Pretrained Protein Language Model Embeddings. MLCB 2022: 110-130 - Ethan Weinberger, Romain Lopez, Jan-Christian Hütter, Aviv Regev:
Disentangling shared and group-specific variations in single-cell transcriptomics data with multiGroupVI. MLCB 2022: 16-32 - Lauren Berk Wheelock, Stephen Malina, Jeffrey Gerold, Sam Sinai:
Forecasting labels under distribution-shift for machine-guided sequence design. MLCB 2022: 166-180
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