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ORCIDElham Azizi
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2020 – today
- 2024
[c6]Achille Nazaret, Justin Hong, Elham Azizi, David M. Blei:
Stable Differentiable Causal Discovery. ICML 2024- [c5]Cameron Park, Shouvik Mani, Nicolas Beltran-Velez, Katie Maurer, Satyen Gohil, Shuqiang Li, Teddy Huang, David A. Knowles, Catherine J. Wu, Elham Azizi:
DIISCO: A Bayesian Framework for Inferring Dynamic Intercellular Interactions from Time-Series Single-Cell Data. RECOMB 2024: 390-395 - 2023
- [j5]Yining Liu, Yinuo Jin, Elham Azizi, Andrew J. Blumberg:
Cellstitch: 3D cellular anisotropic image segmentation via optimal transport. BMC Bioinform. 24(1): 480 (2023) - [j4]Md. Yousuf Hossain, Elham Azizi, Loutfouz Zaman:
Predicting subscription renewal using binary classification in World of Warcraft. Entertain. Comput. 44: 100522 (2023) - [j3]Elham Azizi
, Loutfouz Zaman:
Deep Learning Pet Identification Using Face and Body. Inf. 14(5): 278 (2023) - [c4]Elham Azizi, Loutfouz Zaman:
Automatic Bug Detection in Games using LSTM Networks. CoG 2023: 1-4 - [i5]Achille Nazaret, Justin Hong, Elham Azizi, David M. Blei:
Stable Differentiable Causal Discovery. CoRR abs/2311.10263 (2023) - [i4]Elham Azizi, Loutfouz Zaman:
Automatic Bug Detection in Games using LSTM Networks. CoRR abs/2312.08418 (2023) - 2022
- [c3]Elham Azizi, Loutfouz Zaman:
Data Analysis and Friendship Prediction for Twitch Streamers. GEM 2022: 1-6 - 2020
- [i3]Ramtin Babaeipour, Elham Azizi, Hassan Khotanlou:
An Empirical Study on Detecting COVID-19 in Chest X-ray Images Using Deep Learning Based Methods. CoRR abs/2010.04936 (2020)
2010 – 2019
- 2019
- [j2]Abdoulaye Baniré Diallo, Engelbert Mephu Nguifo, Wajdi Dhifli, Elham Azizi, Sandhya Prabhakaran, Wesley Tansey:
Selected Papers from the Workshop on Computational Biology: Joint with the International Joint Conference on Artificial Intelligence and the International Conference on Machine Learning, 2018. J. Comput. Biol. 26(6): 507-508 (2019) - [i2]Cassandra Burdziak, Elham Azizi, Sandhya Prabhakaran, Dana Pe'er:
A Nonparametric Multi-view Model for Estimating Cell Type-Specific Gene Regulatory Networks. CoRR abs/1902.08138 (2019) - 2016
- [c2]Sandhya Prabhakaran, Elham Azizi, Ambrose J. Carr, Dana Pe'er:
Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data. ICML 2016: 1070-1079 - 2014
- [b1]Elham Azizi:
Modeling gene regulatory networks through data integration. Boston University, USA, 2014 - [c1]Elham Azizi, Edoardo M. Airoldi, James E. Galagan:
Learning Modular Structures from Network Data and Node Variables. ICML 2014: 1440-1448 - [i1]Elham Azizi, James E. Galagan, Edoardo M. Airoldi:
Learning modular structures from network data and node variables. CoRR abs/1405.2566 (2014) - 2013
- [j1]James E. Galagan, Kyle J. Minch, Matthew Peterson, Anna Lyubetskaya, Elham Azizi, Linsday Sweet, Antonio Gomes, Tige R. Rustad, Gregory Dolganov, Irina Glotova, Thomas Abeel, Chris Mahwinney, Adam D. Kennedy, René Allard, William Brabant, Andrew Krueger, Suma Jaini, Brent Honda, Wen-Han Yu, Mark J. Hickey, Jeremy Zucker, Christopher Garay, Brian Weiner, Peter Sisk, Christian Stolte, Jessica K. Winkler, Yves Van de Peer, Paul Iazzetti, Diogo Camacho, Jonathan M. Dreyfuss, Yang Liu, Anca Dorhoi, Hans-Joachim Mollenkopf, Paul Drogaris, Julie Lamontagne, Yiyong Zhou, Julie Piquenot, Sang Tae Park, Sahadevan Raman, Stefan H. E. Kaufmann, Robert P. Mohney, Daniel Chelsky, D. Branch Moody, David R. Sherman, Gary K. Schoolnik:
The Mycobacterium tuberculosis regulatory network and hypoxia. Nat. 499(7457): 178-183 (2013)
Coauthor Index
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