Matt J. Kusner

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Kilian WeinbergerCornell UniversityVerified email at cornell.edu
Ricardo SilvaProfessor of Statistical Machine Learning and Data Science, Department of Statistical Science, UCLVerified email at stats.ucl.ac.uk
José Miguel Hernández-LobatoProfessor of Machine Learning, University of CambridgeVerified email at cam.ac.uk
Joshua LoftusLondon School of EconomicsVerified email at lse.ac.uk
Brooks PaigeAssociate Professor, University College LondonVerified email at ucl.ac.uk
Chris RussellAssociate Professor, University of OxfordVerified email at oii.ox.ac.uk
Yu SunPostdoc, Stanford UniversityVerified email at cs.stanford.edu
Zhixiang (Eddie) XuWashington UniversityVerified email at cse.wustl.edu
Nicholas KolkinResearch Engineer, AdobeVerified email at adobe.com
Adrià GascónGoogle ResearchVerified email at google.com
Jacob GardnerUniversity of PennsylvaniaVerified email at seas.upenn.edu
Arthur GrettonGatsby Computational Neuroscience Unit and Google DeepmindVerified email at gatsby.ucl.ac.uk
Limor GultchinUniversity of Oxford; The Alan Turing InstituteVerified email at cs.ox.ac.uk
Gao Huang （黄高）Associate Professor, Tsinghua UniversityVerified email at tsinghua.edu.cn
Stephen TyreeNVIDIAVerified email at nvidia.com
Vlad NiculaeUniversity of AmsterdamVerified email at uva.nl
Roman GarnettWashington University in St. LouisVerified email at wustl.edu
Sanmi KoyejoAssistant Professor, Stanford UniversityVerified email at stanford.edu
Alexander D'AmourResearch Scientist, Google DeepMindVerified email at google.com
Jessica SchrouffDeepMindVerified email at deepmind.com

Matt J. Kusner

University College London

Verified email at ucl.ac.uk - Homepage

machine learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
From word embeddings to document distances M Kusner, Y Sun, N Kolkin, K Weinberger International conference on machine learning, 957-966, 2015	2855	2015
Counterfactual fairness MJ Kusner, J Loftus, C Russell, R Silva Advances in neural information processing systems 30, 2017	2031	2017
Grammar variational autoencoder MJ Kusner, B Paige, JM Hernández-Lobato International conference on machine learning, 1945-1954, 2017	1090	2017
Bayesian optimization with inequality constraints. JR Gardner, MJ Kusner, ZE Xu, KQ Weinberger, JP Cunningham ICML 2014, 937-945, 2014	580	2014
Gans for sequences of discrete elements with the gumbel-softmax distribution MJ Kusner, JM Hernández-Lobato arXiv preprint arXiv:1611.04051, 2016	382	2016
Unsupervised point cloud pre-training via occlusion completion H Wang, Q Liu, X Yue, J Lasenby, MJ Kusner Proceedings of the IEEE/CVF international conference on computer vision …, 2021	267	2021
QUOTIENT: Two-party secure neural network training and prediction N Agrawal, A Shahin Shamsabadi, MJ Kusner, A Gascón Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019	245	2019
Supervised Word Mover's Distance G Huang, C Guo, MJ Kusner, Y Sun, F Sha, KQ Weinberger Advances in Neural Information Processing Systems, 3270-3278, 2016	240	2016
A survey on contextual embeddings Q Liu, MJ Kusner, P Blunsom arXiv preprint arXiv:2003.07278, 2020	239	2020
When worlds collide: integrating different counterfactual assumptions in fairness C Russell, MJ Kusner, J Loftus, R Silva Advances in neural information processing systems 30, 2017	212	2017
Blind justice: fairness with encrypted sensitive attributes N Kilbertus, A Gascón, MJ Kusner, M Veale, KP Gummadi, A Weller ICML, 2018	169	2018
Causal reasoning for algorithmic fairness JR Loftus, C Russell, MJ Kusner, R Silva arXiv preprint arXiv:1805.05859, 2018	165	2018
TAPAS: tricks to accelerate (encrypted) prediction as a service A Sanyal, MJ Kusner, A Gascón, V Kanade ICML, 2018	162	2018
Cost-sensitive tree of classifiers Z Xu, M Kusner, K Weinberger, M Chen International conference on machine learning, 133-141, 2013	149	2013
Causal machine learning: A survey and open problems J Kaddour, A Lynch, Q Liu, MJ Kusner, R Silva arXiv preprint arXiv:2206.15475, 2022	137	2022
A model to search for synthesizable molecules J Bradshaw, B Paige, MJ Kusner, M Segler, JM Hernández-Lobato Advances in Neural Information Processing Systems 32, 2019	124	2019
Classifier cascades and trees for minimizing feature evaluation cost Z Xu, MJ Kusner, KQ Weinberger, M Chen, O Chapelle The Journal of Machine Learning Research 15 (1), 2113-2144, 2014	109	2014
Fast distributed k-center clustering with outliers on massive data G Malkomes, MJ Kusner, W Chen, KQ Weinberger, B Moseley Advances in Neural Information Processing Systems 28, 2015	97	2015
The long road to fairer algorithms MJ Kusner, JR Loftus Nature 578 (7793), 34-36, 2020	96	2020
Stochastic neighbor compression M Kusner, S Tyree, K Weinberger, K Agrawal International conference on machine learning, 622-630, 2014	90	2014

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