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ORCIDMLCB 2023: Seattle, WA, USA
- 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 - Zachary S. Sims, Young Hwan Chang:
A Masked Image Modeling Approach to CyCIF Panel Reduction and Marker Imputation. 1-9 - You Wu, Omid Bazgir, Yongju Lee, Tommaso Biancalani, James Lu, Ehsan Hajiramezanali:
Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction. 10-22 - Renming Liu, Arjun Krishnan:
Open Biomedical Network Benchmark: A Python Toolkit for Benchmarking Datasets with Biomedical Networks. 23-59 - Kaspar Märtens, Christopher Yau:
Disentangling shared and private latent factors in multimodal Variational Autoencoders. 60-75 - Andrea Nathansen, Kevin Klein, Bernhard Y. Renard, Melania Nowicka, Jakub M. Bartoszewicz:
Evaluating Tuning Strategies for Sequence Generation with Protein Language Models. 76-89 - 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. 90-100 - Ethar Alzaid, Muhammad Dawood, Fayyaz Minhas:
A Transductive Approach to Survival Ranking for Cancer Risk Stratification. 101-109 - Antoine Szatkownik, Cyril Furtlehner, Guillaume Charpiat, Burak Yelmen
, Flora Jay:
Towards creating longer genetic sequences with GANs: Generation in principal component space. 110-122 - 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? 123-134 - Jennifer Yu, Zhenqin Wu, Aaron T. Mayer, Alexandro Trevino, James Zou:
A Multi-Granularity Approach to Similarity Search in Multiplexed Immunofluorescence Images. 135-147 - Chenwei Zhang, Jordan Lovrod, Boyan Beronov, Khanh Dao Duc, Anne Condon:
ViDa: Visualizing DNA hybridization trajectories with biophysics-informed deep graph embeddings. 148-162 - Keren Isaev, David A. Knowles:
Investigating RNA splicing as a source of cellular diversity using a binomial mixture model. 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. 176-193 - 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. 194-229 - Gian Marco Visani, William Galvin, Michael N. Pun, Armita Nourmohammad:
H-Packer: Holographic Rotationally Equivariant Convolutional Neural Network for Protein Side-Chain Packing. 230-249 - Eyes S. Robson, Nilah Ioannidis:
GUANinE v1.0: Benchmark Datasets for Genomic AI Sequence-to-Function Models. 250-266 - Juneki Hong, Dezhong Deng, David A. Hendrix:
Improving transformer secondary structure predictions with secondary structure "fixing" task. 267-278 - Ayesha Bajwa, Ruchir Rastogi, Pooja Kathail, Richard W. Shuai, Nilah Ioannidis:
Characterizing uncertainty in predictions of genomic sequence-to-activity models. 279-297
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last updated on 2024-11-19 20:32 CET by the dblp team
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