Kusner, Matt J.

21 publications

AISTATS 2023 Adapting to Latent Subgroup Shifts via Concepts and Proxies Ibrahim Alabdulmohsin, Nicole Chiou, Alexander D’Amour, Arthur Gretton, Sanmi Koyejo, Matt J. Kusner, Stephen R. Pfohl, Olawale Salaudeen, Jessica Schrouff, Katherine Tsai

NeurIPS 2023 No Train No Gain: Revisiting Efficient Training Algorithms for Transformer-Based Language Models Jean Kaddour, Oscar Key, Piotr Nawrot, Pasquale Minervini, Matt J Kusner

UAI 2022 Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva

NeurIPS 2022 Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus, Haydn Jones, Juston Moore, Matt J Kusner, John Bradshaw, Jacob Gardner

NeurIPS 2022 When Do Flat Minima Optimizers Work? Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J Kusner

NeurIPS 2021 Causal Effect Inference for Structured Treatments Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J Kusner, Ricardo Silva

ICCV 2021 Unsupervised Point Cloud Pre-Training via Occlusion Completion Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matt J. Kusner

NeurIPS 2020 A Class of Algorithms for General Instrumental Variable Models Niki Kilbertus, Matt J Kusner, Ricardo Silva

NeurIPS 2020 Barking up the Right Tree: An Approach to Search over Molecule Synthesis DAGs John Bradshaw, Brooks Paige, Matt J Kusner, Marwin Segler, José Miguel Hernández-Lobato

ICLR 2019 A Generative Model for Electron Paths John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato

NeurIPS 2019 A Model to Search for Synthesizable Molecules John Bradshaw, Brooks Paige, Matt J Kusner, Marwin Segler, José Miguel Hernández-Lobato

ICLRW 2019 Generating Molecules via Chemical Reactions John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, José Miguel Hernández-Lobato

UAI 2019 The Sensitivity of Counterfactual Fairness to Unmeasured Confounding Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva

NeurIPS 2017 Counterfactual Fairness Matt J Kusner, Joshua Loftus, Chris Russell, Ricardo Silva

ICML 2017 Grammar Variational Autoencoder Matt J. Kusner, Brooks Paige, José Miguel Hernández-Lobato

NeurIPS 2017 When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness Chris Russell, Matt J Kusner, Joshua Loftus, Ricardo Silva

AISTATS 2016 Private Causal Inference Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger

NeurIPS 2016 Supervised Word Mover's Distance Gao Huang, Chuan Guo, Matt J Kusner, Yu Sun, Fei Sha, Kilian Q. Weinberger

NeurIPS 2015 Fast Distributed K-Center Clustering with Outliers on Massive Data Gustavo Malkomes, Matt J Kusner, Wenlin Chen, Kilian Q. Weinberger, Benjamin Moseley

JMLR 2014 Classifier Cascades and Trees for Minimizing Feature Evaluation Cost Zhixiang Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen, Olivier Chapelle

AAAI 2014 Feature-Cost Sensitive Learning with Submodular Trees of Classifiers Matt J. Kusner, Wenlin Chen, Quan Zhou, Zhixiang Eddie Xu, Kilian Q. Weinberger, Yixin Chen