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ORCIDMohammad Taha Bahadori
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2020 – today
- 2024
[c21]Victor Quintas-Martinez, Mohammad Taha Bahadori, Eduardo Santiago, Jeff Mu, David Heckerman:
Multiply-Robust Causal Change Attribution. ICML 2024- [i14]Victor Quintas-Martinez, Mohammad Taha Bahadori, Eduardo Santiago, Jeff Mu, Dominik Janzing, David Heckerman:
Multiply-Robust Causal Change Attribution. CoRR abs/2404.08839 (2024) - [i13]Milad Fotouhi, Mohammad Taha Bahadori, Oluwaseyi Feyisetan, Payman Arabshahi, David Heckerman:
Fast Training Dataset Attribution via In-Context Learning. CoRR abs/2408.11852 (2024) - 2022
- [c20]Mohammad Taha Bahadori, Eric Tchetgen Tchetgen, David Heckerman:
End-to-End Balancing for Causal Continuous Treatment-Effect Estimation. ICML 2022: 1313-1326 - 2021
- [c19]Mohammad Taha Bahadori, David Heckerman:
Debiasing Concept-based Explanations with Causal Analysis. ICLR 2021 - [i12]Mohammad Taha Bahadori, Eric Tchetgen Tchetgen, David E. Heckerman:
End-to-End Balancing for Causal Continuous Treatment-Effect Estimation. CoRR abs/2107.13068 (2021) - 2020
- [i11]Mohammad Taha Bahadori, David E. Heckerman:
Debiasing Concept Bottleneck Models with Instrumental Variables. CoRR abs/2007.11500 (2020)
2010 – 2019
- 2019
- [j2]Zemin Zheng, Mohammad Taha Bahadori, Yan Liu, Jinchi Lv:
Scalable Interpretable Multi-Response Regression via SEED. J. Mach. Learn. Res. 20: 107:1-107:34 (2019) - [i10]Mohammad Taha Bahadori, Zachary Chase Lipton:
Temporal-Clustering Invariance in Irregular Healthcare Time Series. CoRR abs/1904.12206 (2019) - [i9]Mohammad Taha Bahadori, Layne C. Price:
Discovering Invariances in Healthcare Neural Networks. CoRR abs/1911.03295 (2019) - 2018
- [i8]Mengqi Jin, Mohammad Taha Bahadori, Aaron Colak, Parminder Bhatia, Busra Celikkaya, Ram Bhakta, Selvan Senthivel, Mohammed Khalilia, Daniel Navarro, Borui Zhang, Tiberiu Doman, Arun Ravi, Matthieu Liger, Taha A. Kass-Hout
:
Improving Hospital Mortality Prediction with Medical Named Entities and Multimodal Learning. CoRR abs/1811.12276 (2018) - 2017
- [c18]Yanbo Xu, Mohammad Taha Bahadori, Elizabeth Searles, Michael Thompson, Javier Tejedor-Sojo, Jimeng Sun:
Predicting Changes in Pediatric Medical Complexity using Large Longitudinal Health Records. AMIA 2017 - [c17]Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun:
GRAM: Graph-based Attention Model for Healthcare Representation Learning. KDD 2017: 787-795 - [p1]Zhengping Che, Sanjay Purushotham, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Robinder G. Khemani, Yan Liu:
Time Series Feature Learning with Applications to Health Care. Mobile Health - Sensors, Analytic Methods, and Applications 2017: 389-409 - [i7]Mohammad Taha Bahadori, Krzysztof Chalupka, Edward Choi, Robert Chen, Walter F. Stewart, Jimeng Sun:
Causal Regularization. CoRR abs/1702.02604 (2017) - 2016
- [c16]Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles, Catherine Coffey, Michael Thompson, James Bost, Javier Tejedor-Sojo, Jimeng Sun:
Multi-layer Representation Learning for Medical Concepts. KDD 2016: 1495-1504 - [c15]Yuyu Zhang, Mohammad Taha Bahadori, Hang Su, Jimeng Sun:
FLASH: Fast Bayesian Optimization for Data Analytic Pipelines. KDD 2016: 2065-2074 - [c14]Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun:
Doctor AI: Predicting Clinical Events via Recurrent Neural Networks. MLHC 2016: 301-318 - [c13]Edward Choi, Mohammad Taha Bahadori, Jimeng Sun, Joshua Kulas, Andy Schuetz, Walter F. Stewart:
RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism. NIPS 2016: 3504-3512 - [i6]Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles, Catherine Coffey, Jimeng Sun:
Multi-layer Representation Learning for Medical Concepts. CoRR abs/1602.05568 (2016) - [i5]Yuyu Zhang, Mohammad Taha Bahadori, Hang Su, Jimeng Sun:
FLASH: Fast Bayesian Optimization for Data Analytic Pipelines. CoRR abs/1602.06468 (2016) - [i4]Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun:
RETAIN: Interpretable Predictive Model in Healthcare using Reverse Time Attention Mechanism. CoRR abs/1608.05745 (2016) - [i3]Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun:
GRAM: Graph-based Attention Model for Healthcare Representation Learning. CoRR abs/1611.07012 (2016) - 2015
- [c12]David C. Kale, Zhengping Che, Mohammad Taha Bahadori, Wenzhe Li, Yan Liu, Randall C. Wetzel:
Causal Phenotype Discovery via Deep Networks. AMIA 2015 - [c11]Mohammad Taha Bahadori, David C. Kale, Yingying Fan, Yan Liu:
Functional Subspace Clustering with Application to Time Series. ICML 2015: 228-237 - [c10]Zhengping Che, David C. Kale, Wenzhe Li, Mohammad Taha Bahadori, Yan Liu:
Deep Computational Phenotyping. KDD 2015: 507-516 - [i2]Edward Choi, Mohammad Taha Bahadori, Jimeng Sun:
Doctor AI: Predicting Clinical Events via Recurrent Neural Networks. CoRR abs/1511.05942 (2015) - 2014
- [j1]Mohammad Taha Bahadori, Yan Liu, Dan Zhang:
A general framework for scalable transductive transfer learning. Knowl. Inf. Syst. 38(1): 61-83 (2014) - [c9]Mohammad Taha Bahadori, Yi Chang, Bo Long, Yan Liu:
Scalable Heterogeneous Transfer Ranking. BigMine 2014: 214-228 - [c8]Dehua Cheng, Mohammad Taha Bahadori, Yan Liu:
FBLG: a simple and effective approach for temporal dependence discovery from time series data. KDD 2014: 382-391 - [c7]Mohammad Taha Bahadori, Qi Rose Yu, Yan Liu:
Fast Multivariate Spatio-temporal Analysis via Low Rank Tensor Learning. NIPS 2014: 3491-3499 - 2013
- [c6]Mohammad Taha Bahadori, Yan Liu, Eric P. Xing:
Fast structure learning in generalized stochastic processes with latent factors. KDD 2013: 284-292 - [c5]Yan Liu, Mohammad Taha Bahadori:
An Examination of Practical Granger Causality Inference. SDM 2013: 467-475 - 2012
- [c4]Mohammad Taha Bahadori, Yan Liu:
On Causality Inference in Time Series. AAAI Fall Symposium: Discovery Informatics 2012 - [c3]Yan Liu, Mohammad Taha Bahadori, Hongfei Li:
Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling. ICML 2012 - [c2]Mohammad Taha Bahadori, Yan Liu:
Granger Causality Analysis in Irregular Time Series. SDM 2012: 660-671 - [i1]Yan Liu, Mohammad Taha Bahadori, Hongfei Li:
Sparse-GEV: Sparse Latent Space Model for Multivariate Extreme Value Time Serie Modeling. CoRR abs/1206.4685 (2012) - 2011
- [c1]Mohammad Taha Bahadori, Yan Liu, Dan Zhang:
Learning with Minimum Supervision: A General Framework for Transductive Transfer Learning. ICDM 2011: 61-70
Coauthor Index
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last updated on 2024-09-30 00:09 CEST by the dblp team
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