Yixin Wang - RankMe

72 papers A* 15A 6Misc 1Journal 45Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Breaking Feedback Loops in Recommender Systems with Causal Inference. Trans. Recomm. Syst. Karl Krauth, Yixin Wang, Michael I. Jordan
2025	J	`jnl`	Bayesian Invariance Modeling of Multi-Environment Data. CoRR Luhuan Wu, Mingzhang Yin, Yixin Wang, John P. Cunningham, David M. Blei
2025	A	`conf`	CONSEQUENCES 2025 - The 4th Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. RecSys Harrie Oosterhuis, Olivier Jeunen, Yuta Saito, Yixin Wang, Flavian Vasile, Thorsten Joachims
2025	J	`jnl`	Exponential Family Attention. CoRR Kevin Christian Wibisono, Yixin Wang
2025	A	`conf`	Posterior Mean Matching: Generative Modeling through Online Bayesian Inference. AISTATS Sebastian Salazar, Michal Kucer, Yixin Wang, Emily M. Casleton, David M. Blei
2025	A*	`conf`	Representation Learning: A Causal Perspective. AAAI Yixin Wang
2024	—	`conf`	A causality-inspired plus-minus model for player evaluation in team sports. CLeaR Caterina De Bacco, Yixin Wang, David M. Blei
2024	A	`conf`	CONSEQUENCES - The 3rd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. RecSys Olivier Jeunen, Harrie Oosterhuis, Yuta Saito, Flavian Vasile, Yixin Wang
2024	J	`jnl`	Causal fairness assessment of treatment allocation with electronic health records. J. Biomed. Informatics Linying Zhang, Lauren R. Richter, Yixin Wang, Anna Ostropolets, Noémie Elhadad, David M. Blei, George Hripcsak
2024	J	`jnl`	Desiderata for Representation Learning: A Causal Perspective. J. Mach. Learn. Res. Yixin Wang, Michael I. Jordan
2024	A*	`conf`	From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When. NeurIPS Kevin Christian Wibisono, Yixin Wang
2024	J	`jnl`	How In-Context Learning Emerges from Training on Unstructured Data: On the Role of Co-Occurrence, Positional Information, and Noise Structures. CoRR Kevin Christian Wibisono, Yixin Wang
2024	J	`jnl`	Instrumental Variable Value Iteration for Causal Offline Reinforcement Learning. J. Mach. Learn. Res. Luofeng Liao, Zuyue Fu, Zhuoran Yang, Yixin Wang, Dingli Ma, Mladen Kolar, Zhaoran Wang
2024	J	`jnl`	Optimization-based Causal Estimation from Heterogeneous Environments. J. Mach. Learn. Res. Mingzhang Yin, Yixin Wang, David M. Blei
2024	J	`jnl`	Posterior Mean Matching: Generative Modeling through Online Bayesian Inference. CoRR Sebastian Salazar, Michal Kucer, Yixin Wang, Emily M. Casleton, David M. Blei
2023	J	`jnl`	Addressing Hindsight Bias in Multigoal Reinforcement Learning. IEEE Trans. Cybern. Chenjia Bai, Lingxiao Wang, Yixin Wang, Zhaoran Wang, Rui Zhao, Chenyao Bai, Peng Liu
2023	J	`jnl`	Adjusting Machine Learning Decisions for Equal Opportunity and Counterfactual Fairness. Trans. Mach. Learn. Res. Yixin Wang, Dhanya Sridhar, David M. Blei
2023	A	`conf`	Bidirectional Attention as a Mixture of Continuous Word Experts. UAI Kevin Christian Wibisono, Yixin Wang
2023	J	`jnl`	Bidirectional Attention as a Mixture of Continuous Word Experts. CoRR Kevin Christian Wibisono, Yixin Wang
2023	A	`conf`	CONSEQUENCES - The 2nd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems. RecSys Olivier Jeunen, Thorsten Joachims, Harrie Oosterhuis, Yuta Saito, Flavian Vasile, Yixin Wang
2023	J	`jnl`	Clarifying Trust of Materials Property Predictions using Neural Networks with Distribution-Specific Uncertainty Quantification. CoRR Cameron J. Gruich, Varun Madhavan, Yixin Wang, Bryan R. Goldsmith
2023	J	`jnl`	Clarifying trust of materials property predictions using neural networks with distribution-specific uncertainty quantification. Mach. Learn. Sci. Technol. Cameron J. Gruich, Varun Madhavan, Yixin Wang, Bryan R. Goldsmith
2023	—	`conf`	Delayed and Indirect Impacts of Link Recommendations. FAccT Han Zhang, Shangen Lu, Yixin Wang, Mihaela Curmei
2023	J	`jnl`	Learning Equilibria in Matching Markets with Bandit Feedback. J. ACM Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt
2023	A*	`conf`	On Learning Necessary and Sufficient Causal Graphs. NeurIPS Hengrui Cai, Yixin Wang, Michael I. Jordan, Rui Song
2023	J	`jnl`	On Learning Necessary and Sufficient Causal Graphs. CoRR Hengrui Cai, Yixin Wang, Michael I. Jordan, Rui Song
2023	J	`jnl`	Posterior Collapse and Latent Variable Non-identifiability. CoRR Yixin Wang, David M. Blei, John P. Cunningham
2023	—	`conf`	Recommendation Systems with Distribution-Free Reliability Guarantees. COPA Anastasios N. Angelopoulos, Karl Krauth, Stephen Bates, Yixin Wang, Michael I. Jordan
2023	A*	`conf`	The Sample Complexity of Online Contract Design. EC Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan
2022	J	`jnl`	A Bayesian Causal Inference Approach for Assessing Fairness in Clinical Decision-Making. CoRR Linying Zhang, Lauren R. Richter, Yixin Wang, Anna Ostropolets, Noemie Elhadad, David M. Blei, George Hripcsak
2022	J	`jnl`	Adjusting for indirectly measured confounding using large-scale propensity score. J. Biomed. Informatics Linying Zhang, Yixin Wang, Martijn J. Schuemie, David M. Blei, George Hripcsak
2022	A*	`conf`	Anticipating Performativity by Predicting from Predictions. NeurIPS Celestine Mendler-Dünner, Frances Ding, Yixin Wang
2022	J	`jnl`	Breaking Feedback Loops in Recommender Systems with Causal Inference. CoRR Karl Krauth, Yixin Wang, Michael I. Jordan
2022	A*	`conf`	Empirical Gateaux Derivatives for Causal Inference. NeurIPS Michael I. Jordan, Yixin Wang, Angela Zhou
2022	J	`jnl`	Empirical Gateaux Derivatives for Causal Inference. CoRR Michael I. Jordan, Yixin Wang, Angela Zhou
2022	J	`jnl`	Identifiable Deep Generative Models via Sparse Decoding. Trans. Mach. Learn. Res. Gemma E. Moran, Dhanya Sridhar, Yixin Wang, David M. Blei
2022	J	`jnl`	Multi-Source Causal Inference Using Control Variates under Outcome Selection Bias. Trans. Mach. Learn. Res. Wenshuo Guo, Serena Lutong Wang, Peng Ding, Yixin Wang, Michael I. Jordan
2022	—	`conf`	Partial Identification with Noisy Covariates: A Robust Optimization Approach. CLeaR Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan
2022	J	`jnl`	Partial Identification with Noisy Covariates: A Robust Optimization Approach. CoRR Wenshuo Guo, Mingzhang Yin, Yixin Wang, Michael I. Jordan
2022	J	`jnl`	Predicting from Predictions. CoRR Celestine Mendler-Dünner, Frances Ding, Yixin Wang
2022	J	`jnl`	Recommendation Systems with Distribution-Free Reliability Guarantees. CoRR Anastasios N. Angelopoulos, Karl Krauth, Stephen Bates, Yixin Wang, Michael I. Jordan
2022	J	`jnl`	The Sample Complexity of Online Contract Design. CoRR Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan
2022	J	`jnl`	Valid Inference after Causal Discovery. CoRR Paula Gradu, Tijana Zrnic, Yixin Wang, Michael I. Jordan
2021	A*	`conf`	A Proxy Variable View of Shared Confounding. ICML Yixin Wang, David M. Blei
2021	A*	`conf`	Bayesian Causal Inference for Real World Interactive Systems. KDD Nicolas Chopin, Mike Gartrell, Dawen Liang, Alberto Lumbreras, David Rohde, Yixin Wang
2021	J	`jnl`	Desiderata for Representation Learning: A Causal Perspective. CoRR Yixin Wang, Michael I. Jordan
2021	J	`jnl`	Identifiable Variational Autoencoders via Sparse Decoding. CoRR Gemma E. Moran, Dhanya Sridhar, Yixin Wang, David M. Blei
2021	A*	`conf`	Learning Equilibria in Matching Markets from Bandit Feedback. NeurIPS Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt
2021	J	`jnl`	Learning Equilibria in Matching Markets from Bandit Feedback. CoRR Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael I. Jordan, Jacob Steinhardt
2021	J	`jnl`	Multi-Source Causal Inference Using Control Variates. CoRR Wenshuo Guo, Serena Lutong Wang, Peng Ding, Yixin Wang, Michael I. Jordan
2021	J	`jnl`	Optimization-based Causal Estimation from Heterogenous Environments. CoRR Mingzhang Yin, Yixin Wang, David M. Blei
2021	A*	`conf`	Posterior Collapse and Latent Variable Non-identifiability. NeurIPS Yixin Wang, David M. Blei, John P. Cunningham
2020	A	`conf`	Causal Inference for Recommender Systems. RecSys Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei
2020	Misc	`conf`	The Multi-Outcome Medical Deconfounder: Assessing Treatment Effect on Multiple Renal Measures. AMIA Linying Zhang, Yixin Wang, Anna Ostropolets, Ruijun Chen, David M. Blei, George Hripcsak
2020	J	`jnl`	Towards Clarifying the Theory of the Deconfounder. CoRR Yixin Wang, David M. Blei
2019	J	`jnl`	Equal Opportunity and Affirmative Action via Counterfactual Predictions. CoRR Yixin Wang, Dhanya Sridhar, David M. Blei
2019	J	`jnl`	Multiple Causes: A Causal Graphical View. CoRR Yixin Wang, David M. Blei
2019	J	`jnl`	The Blessings of Multiple Causes: A Reply to Ogburn et al. (2019). CoRR Yixin Wang, David M. Blei
2019	J	`jnl`	The Medical Deconfounder: Assessing Treatment Effect with Electronic Health Records (EHRs). CoRR Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak
2019	—	`conf`	The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records. MLHC Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak
2019	A*	`conf`	Using Embeddings to Correct for Unobserved Confounding in Networks. NeurIPS Victor Veitch, Yixin Wang, David M. Blei
2019	J	`jnl`	Using Embeddings to Correct for Unobserved Confounding. CoRR Victor Veitch, Yixin Wang, David M. Blei
2019	A*	`conf`	Variational Bayes under Model Misspecification. NeurIPS Yixin Wang, David M. Blei
2019	J	`jnl`	Variational Bayes under Model Misspecification. CoRR Yixin Wang, David M. Blei
2018	A*	`conf`	Black Box FDR. ICML Wesley Tansey, Yixin Wang, David M. Blei, Raul Rabadan
2018	J	`jnl`	Black Box FDR. CoRR Wesley Tansey, Yixin Wang, David M. Blei, Raul Rabadan
2018	J	`jnl`	The Blessings of Multiple Causes. CoRR Yixin Wang, David M. Blei
2018	J	`jnl`	The Deconfounded Recommender: A Causal Inference Approach to Recommendation. CoRR Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei
2017	A*	`conf`	Evaluating Bayesian Models with Posterior Dispersion Indices. ICML Alp Kucukelbir, Yixin Wang, David M. Blei
2017	J	`jnl`	Frequentist Consistency of Variational Bayes. CoRR Yixin Wang, David M. Blei
2017	A*	`conf`	Robust Probabilistic Modeling with Bayesian Data Reweighting. ICML Yixin Wang, Alp Kucukelbir, David M. Blei
2016	J	`jnl`	Reweighted Data for Robust Probabilistic Models. CoRR Yixin Wang, Alp Kucukelbir, David M. Blei