Matt J. Kusner
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
31
Venues
8
Active years
2013–2025
Best venue rank
A*
Where they publish
Papers
31 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | An Auditing Test to Detect Behavioral Shift in Language Models. | Leo Richter, Xuanli He, Pasquale Minervini, Matt J. Kusner |
| 2025 | ICML | Calibrated Physics-Informed Uncertainty Quantification. | Vignesh Gopakumar, Ander Gray, Lorenzo Zanisi, Timothy Nunn, Daniel Giles, Matt J. Kusner, Stanislas Pamela, Marc Peter Deisenroth |
| 2025 | ICML | When Can Proxies Improve the Sample Complexity of Preference Learning? | Yuchen Zhu, Daniel Augusto de Souza, Zhengyan Shi, Mengyue Yang, Pasquale Minervini, Matt J. Kusner, Alexander Nicholas D'Amour |
| 2024 | AISTATS | Proxy Methods for Domain Adaptation. | Katherine Tsai, Stephen R. Pfohl, Olawale Salaudeen, Nicole Chiou, Matt J. Kusner, Alexander D'Amour, Sanmi Koyejo, Arthur Gretton |
| 2023 | AISTATS | 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 |
| 2023 | ICLR | DAG Learning on the Permutahedron. | Valentina Zantedeschi, Luca Franceschi, Jean Kaddour, Matt J. Kusner, Vlad Niculae |
| 2022 | UAI | Causal inference with treatment measurement error: a nonparametric instrumental variable approach. | Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva |
| 2021 | CCS | MPC-Friendly Commitments for Publicly Verifiable Covert Security. | Nitin Agrawal, James Bell, Adri Gascn, Matt J. Kusner |
| 2021 | ICCV | Unsupervised Point Cloud Pre-training via Occlusion Completion. | Hanchen Wang, Qi Liu, Xiangyu Yue, Joan Lasenby, Matt J. Kusner |
| 2021 | ICML | Operationalizing Complex Causes: A Pragmatic View of Mediation. | Limor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva |
| 2021 | ICML | Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction. | Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet |
| 2021 | ICML | Learning Binary Decision Trees by Argmin Differentiation. | Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae |
| 2021 | NAACL | Counterfactual Data Augmentation for Neural Machine Translation. | Qi Liu, Matt J. Kusner, Phil Blunsom |
| 2020 | AISTATS | Differentiable Causal Backdoor Discovery. | Limor Gultchin, Matt J. Kusner, Varun Kanade, Ricardo Silva |
| 2019 | CCS | QUOTIENT: Two-Party Secure Neural Network Training and Prediction. | Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner, Adri Gascn |
| 2019 | ICLR | A Generative Model For Electron Paths. | John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, Jos Miguel Hernndez-Lobato |
| 2019 | ICLR | Generating Molecules via Chemical Reactions. | John Bradshaw, Matt J. Kusner, Brooks Paige, Marwin H. S. Segler, Jos Miguel Hernndez-Lobato |
| 2019 | ICML | Making Decisions that Reduce Discriminatory Impacts. | Matt J. Kusner, Chris Russell, Joshua R. Loftus, Ricardo Silva |
| 2019 | UAI | The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. | Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva |
| 2018 | ICLR | Learning a Generative Model for Validity in Complex Discrete Structures. | David Janz, Jos van der Westhuizen, Brooks Paige, Matt J. Kusner, Jos Miguel Hernndez-Lobato |
| 2018 | ICML | Blind Justice: Fairness with Encrypted Sensitive Attributes. | Niki Kilbertus, Adri Gascn, Matt J. Kusner, Michael Veale, Krishna P. Gummadi, Adrian Weller |
| 2018 | ICML | TAPAS: Tricks to Accelerate (encrypted) Prediction As a Service. | Amartya Sanyal, Matt J. Kusner, Adri Gascn, Varun Kanade |
| 2017 | ICML | Grammar Variational Autoencoder. | Matt J. Kusner, Brooks Paige, Jos Miguel Hernndez-Lobato |
| 2016 | AISTATS | Private Causal Inference. | Matt J. Kusner, Yu Sun, Karthik Sridharan, Kilian Q. Weinberger |
| 2015 | ICML | Differentially Private Bayesian Optimization. | Matt J. Kusner, Jacob R. Gardner, Roman Garnett, Kilian Q. Weinberger |
| 2015 | ICML | From Word Embeddings To Document Distances. | Matt J. Kusner, Yu Sun, Nicholas I. Kolkin, Kilian Q. Weinberger |
| 2014 | AAAI | Feature-Cost Sensitive Learning with Submodular Trees of Classifiers. | Matt J. Kusner, Wenlin Chen, Quan Zhou, Zhixiang Eddie Xu, Kilian Q. Weinberger, Yixin Chen |
| 2014 | ICML | Bayesian Optimization with Inequality Constraints. | Jacob R. Gardner, Matt J. Kusner, Zhixiang Eddie Xu, Kilian Q. Weinberger, John P. Cunningham |
| 2014 | ICML | Stochastic Neighbor Compression. | Matt J. Kusner, Stephen Tyree, Kilian Q. Weinberger, Kunal Agrawal |
| 2013 | ICML | Anytime Representation Learning. | Zhixiang Eddie Xu, Matt J. Kusner, Gao Huang, Kilian Q. Weinberger |
| 2013 | ICML | Cost-Sensitive Tree of Classifiers. | Zhixiang Eddie Xu, Matt J. Kusner, Kilian Q. Weinberger, Minmin Chen |