Search results for "Confounders"

Hits ?▲	Authors	Title	Venue	Year	Link	Author keywords
21	Takashi Nicholas Maeda, Shohei Shimizu	Causal discovery of linear non-Gaussian acyclic models in the presence of latent confounders.	CoRR	2020	DBLP BibTeX RDF
21	Andreas Gerhardus, Jakob Runge	High-recall causal discovery for autocorrelated time series with latent confounders.	CoRR	2020	DBLP BibTeX RDF
21	Sebastian Pölsterl, Christian Wachinger	Controlling for Unknown Confounders in Neuroimaging.	CoRR	2020	DBLP BibTeX RDF
21	Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze-Yun Leong	A Causal Modeling Framework with Stochastic Confounders.	CoRR	2020	DBLP BibTeX RDF
21	Andrew Bennett, Nathan Kallus, Lihong Li 0001, Ali Mousavi 0003	Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders.	CoRR	2020	DBLP BibTeX RDF
21	Muhammad Ammar Malik, Tom Michoel	Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders.	CoRR	2020	DBLP BibTeX RDF
21	Sam Witty, Kenta Takatsu, David D. Jensen, Vikash Mansinghka 0001	Causal Inference using Gaussian Processes with Structured Latent Confounders.	CoRR	2020	DBLP BibTeX RDF
21	Galen Weld, Peter West, Maria Glenski, David Arbour, Ryan A. Rossi, Tim Althoff	Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference.	CoRR	2020	DBLP BibTeX RDF
21	Shantanu Gupta, Zachary C. Lipton, David Childers	Estimating Treatment Effects with Observed Confounders and Mediators.	CoRR	2020	DBLP BibTeX RDF
21	Ruoqi Liu, Changchang Yin, Ping Zhang 0016	Estimating Individual Treatment Effects with Time-Varying Confounders.	ICDM	2020	DBLP DOI BibTeX RDF
21	Sorawit Saengkyongam, Ricardo Silva	Learning Joint Nonlinear Effects from Single-variable Interventions in the Presence of Hidden Confounders. (PDF / PS)	UAI	2020	DBLP BibTeX RDF
21	Panchapakesan C. Sruthi, Sanjay G. Rao, Bruno Ribeiro 0001	Pitfalls of data-driven networking: A case study of latent causal confounders in video streaming.	NetAI@SIGCOMM	2020	DBLP DOI BibTeX RDF
21	Andreas Gerhardus, Jakob Runge	High-recall causal discovery for autocorrelated time series with latent confounders.	NeurIPS	2020	DBLP BibTeX RDF
21	Aahlad Manas Puli, Adler J. Perotte, Rajesh Ranganath	Causal Estimation with Functional Confounders.	NeurIPS	2020	DBLP BibTeX RDF
21	Junzhe Zhang, Daniel Kumor, Elias Bareinboim	Causal Imitation Learning With Unobserved Confounders.	NeurIPS	2020	DBLP BibTeX RDF
21	Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar	Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders.	ICML	2020	DBLP BibTeX RDF
21	Sam Witty, Kenta Takatsu, David D. Jensen, Vikash Mansinghka 0001	Causal Inference using Gaussian Processes with Structured Latent Confounders.	ICML	2020	DBLP BibTeX RDF
21	Takashi Nicholas Maeda, Shohei Shimizu	RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders.	AISTATS	2020	DBLP BibTeX RDF
21	Florian Schmidt 0003, Marcel H. Schulz	On the problem of confounders in modeling gene expression.	Bioinform.	2019	DBLP DOI BibTeX RDF
21	Yuan Meng	Estimating Granger Causality with Unobserved Confounders via Deep Latent-Variable Recurrent Neural Network.	CoRR	2019	DBLP BibTeX RDF
21	Mimansa Jaiswal, Zakaria Aldeneh, Emily Mower Provost	Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning.	CoRR	2019	DBLP BibTeX RDF
21	Patrick Forré, Joris M. Mooij	Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias.	CoRR	2019	DBLP BibTeX RDF
21	Rathin Desai, Amit Sharma	Quantifying Error in the Presence of Confounders for Causal Inference.	CoRR	2019	DBLP BibTeX RDF
21	Elisa Ferrari, Alessandra Retico, Davide Bacciu	Measuring the effects of confounders in medical supervised classification problems: the Confounding Index (CI).	CoRR	2019	DBLP BibTeX RDF
21	Wenjie Shang, Yang Yu 0001, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye	Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation.	CoRR	2019	DBLP BibTeX RDF
21	Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar	Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders.	CoRR	2019	DBLP BibTeX RDF
21	Andrew Bennett, Nathan Kallus	Policy Evaluation with Latent Confounders via Optimal Balance.	CoRR	2019	DBLP BibTeX RDF
21	Patrick Forré, Joris M. Mooij	Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias. (PDF / PS)	UAI	2019	DBLP BibTeX RDF
21	Mimansa Jaiswal, Zakaria Aldeneh, Emily Mower Provost	Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning.	ICMI	2019	DBLP DOI BibTeX RDF
21	Wenjie Shang, Yang Yu 0001, Qingyang Li, Zhiwei (Tony) Qin, Yiping Meng, Jieping Ye	Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation.	KDD	2019	DBLP DOI BibTeX RDF
21	Andrew Bennett, Nathan Kallus	Policy Evaluation with Latent Confounders via Optimal Balance.	NeurIPS	2019	DBLP BibTeX RDF
21	Patrick Forré, Joris M. Mooij	Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders.	CoRR	2018	DBLP BibTeX RDF
21	Patrick Forré, Joris M. Mooij	Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders.	UAI	2018	DBLP BibTeX RDF
21	Fujin Zhu, Adi Lin, Guangquan Zhang 0001, Jie Lu 0001	Counterfactual Inference with Hidden Confounders Using Implicit Generative Models.	Australasian Conference on Artificial Intelligence	2018	DBLP DOI BibTeX RDF
21	Takashi Isozaki, Manabu Kuroki	Learning Causal Graphs with Latent Confounders in Weak Faithfulness Violations.	New Gener. Comput.	2017	DBLP DOI BibTeX RDF
21	Lingfei Wang, Tom Michoel	Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data.	PLoS Comput. Biol.	2017	DBLP DOI BibTeX RDF
21	Rajat Sen, Karthikeyan Shanmugam, Murat Kocaoglu, Alexandros G. Dimakis, Sanjay Shakkottai	Contextual Bandits with Latent Confounders: An NMF Approach.	AISTATS	2017	DBLP BibTeX RDF
21	Peng Luo, Zhi Geng	Causal mediation analysis for survival outcome with unobserved mediator-outcome confounders.	Comput. Stat. Data Anal.	2016	DBLP DOI BibTeX RDF
21	Moritz Grosse-Wentrup, Dominik Janzing, Markus Siegel, Bernhard Schölkopf	Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach.	NeuroImage	2016	DBLP DOI BibTeX RDF
21	Zheng-Zheng Tang, Guanhua Chen, Alexander V. Alekseyenko	PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances.	Bioinform.	2016	DBLP DOI BibTeX RDF
21	Sofia Triantafillou, Ioannis Tsamardinos	Score-based vs Constraint-based Causal Learning in the Presence of Confounders.	CFA@UAI	2016	DBLP BibTeX RDF
21	Haohan Wang, Jingkang Yang	Multiple confounders correction with regularized linear mixed effect models, with application in biological processes.	BIBM	2016	DBLP DOI BibTeX RDF
21	Limin Li, Shuqin Zhang	Orthogonal projection correction for confounders in biological data classification.	Int. J. Data Min. Bioinform.	2015	DBLP DOI BibTeX RDF
21	Elias Bareinboim, Andrew Forney, Judea Pearl	Bandits with Unobserved Confounders: A Causal Approach.	NIPS	2015	DBLP BibTeX RDF
21	Tatsuya Tashiro, Shohei Shimizu, Aapo Hyvärinen, Takashi Washio	ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders.	Neural Comput.	2014	DBLP DOI BibTeX RDF
21	Geert J. S. Litjens, R. Elliott, Natalie Shih, Michael D. Feldman, Jelle O. Barentsz, Christina A. Hulsbergen van de Kaa, Iringo Kovacs, Henkjan J. Huisman, Anant Madabhushi	Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI.	Medical Imaging: Computer-Aided Diagnosis	2014	DBLP DOI BibTeX RDF
21	Richard Gregg, Saeed Babaeizadeh	Improving Automatic Detection of Acute Myocardial Infarction in the Presence of Confounders. (PDF / PS)	CinC	2014	DBLP BibTeX RDF
21	Prateek Prasanna, Pallavi Tiwari, Anant Madabhushi	Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): Distinguishing Tumor Confounders and Molecular Subtypes on MRI.	MICCAI (3)	2014	DBLP DOI BibTeX RDF
21	Julianna Kohler, Manigandan Easwaran, Gerardo Soto-Campos, Tanmay Gupta, Santhosh Narayanan, Elisabeth Scheufele, Matvey B. Palchuk	A General Propensity Matching Algorithm to Control for Potential Confounders in Observational Studies using Outcomes Miner.	AMIA	2014	DBLP BibTeX RDF
21	Wenan Chen, Guimin Gao, Srilaxmi Nerella, Christina M. Hultman, Patrik K. E. Magnusson, Patrick F. Sullivan, Karolina A. Åberg, Edwin J. C. G. van den Oord	MethylPCA: a toolkit to control for confounders in methylome-wide association studies.	BMC Bioinform.	2013	DBLP DOI BibTeX RDF
21	Zhitang Chen, Laiwan Chan	Causality in Linear Nongaussian Acyclic Models in the Presence of Latent Gaussian Confounders.	Neural Comput.	2013	DBLP DOI BibTeX RDF
21	Jennifer Listgarten, Christoph Lippert, Eun Yong Kang, Jing Xiang, Carl Myers Kadie, David Heckerman	A powerful and efficient set test for genetic markers that handles confounders.	Bioinform.	2013	DBLP DOI BibTeX RDF
21	Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf	Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders.	CoRR	2013	DBLP BibTeX RDF
21	Eleni Sgouritsa, Dominik Janzing, Jonas Peters, Bernhard Schölkopf	Identifying Finite Mixtures of Nonparametric Product Distributions and Causal Inference of Confounders.	UAI	2013	DBLP BibTeX RDF
21	Antti Hyttinen	Discovering Causal Relations in the Presence of Latent Confounders.		2013	RDF
21	Tao Yu, Jialiang Li 0001, Shuangge Ma	Adjusting confounders in ranking biomarkers: a model-based ROC approach.	Briefings Bioinform.	2012	DBLP DOI BibTeX RDF
21	Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf	Identifying confounders using additive noise models	CoRR	2012	DBLP BibTeX RDF
21	Zhitang Chen, Laiwan Chan	Causal Discovery for Linear Non-Gaussian Acyclic Models in the Presence of Latent Gaussian Confounders.	LVA/ICA	2012	DBLP DOI BibTeX RDF
21	Tatsuya Tashiro, Shohei Shimizu, Aapo Hyvärinen, Takashi Washio	Estimation of Causal Orders in a Linear Non-Gaussian Acyclic Model: A Method Robust against Latent Confounders.	ICANN (1)	2012	DBLP DOI BibTeX RDF
21	Jennifer Listgarten, Carl Myers Kadie, Eric E. Schadt, David Heckerman	Correction for Hidden Confounders in the Genetic Analysis of Gene Expression (Abstract).	UAI	2011	DBLP BibTeX RDF
21	Tomoya Higashigaki, Kaname Kojima, Rui Yamaguchi, Masato Inoue, Seiya Imoto, Satoru Miyano	Identifying Hidden Confounders in Gene Networks by Bayesian Networks.	BIBE	2010	DBLP DOI BibTeX RDF	Hidden confounder, Profile infference, Bayesian network, Gene regulatory network, Structural learning
21	Wenjun Zhou 0001, Hui Xiong 0001	Efficient Discovery of Confounders in Large Data Sets.	ICDM	2009	DBLP DOI BibTeX RDF
21	Dominik Janzing, Jonas Peters, Joris M. Mooij, Bernhard Schölkopf	Identifying confounders using additive noise models.	UAI	2009	DBLP BibTeX RDF
21	Jiji Zhang	On the completeness of orientation rules for causal discovery in the presence of latent confounders and selection bias.	Artif. Intell.	2008	DBLP DOI BibTeX RDF
21	Stefanie Scheid, Rainer Spang	Compensating for Unknown Confounders in Microarray Data Analysis Using Filtered Permutations.	J. Comput. Biol.	2007	DBLP DOI BibTeX RDF
21	Dirk Temme	Constraint-based inference algorithms for structural models with latent confounders - empirical application and simulations.	Comput. Stat.	2006	DBLP DOI BibTeX RDF