Matt J. Kusner

Matt J. Kusner

University College London

H-index: 32

Europe-United Kingdom

About Matt J. Kusner

Matt J. Kusner, With an exceptional h-index of 32 and a recent h-index of 31 (since 2020), a distinguished researcher at University College London, specializes in the field of machine learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Proxy Methods for Domain Adaptation

Setting the Record Straight on Transformer Oversmoothing

No train no gain: Revisiting efficient training algorithms for transformer-based language models

Stochastic causal programming for bounding treatment effects

Adapting to latent subgroup shifts via concepts and proxies

DAG Learning on the Permutahedron

When Do Flat Minima Optimizers Work?

Local Latent Space Bayesian Optimization over Structured Inputs

Matt J. Kusner Information

University

Position

Associate Professor

Citations(all)

9043

Citations(since 2020)

7700

Cited By

4034

hIndex(all)

32

hIndex(since 2020)

31

i10Index(all)

41

i10Index(since 2020)

39

Email

University Profile Page

University College London

Google Scholar

View Google Scholar Profile

Matt J. Kusner Skills & Research Interests

machine learning

Top articles of Matt J. Kusner

Title

Journal

Author(s)

Publication Date

Proxy Methods for Domain Adaptation

Katherine Tsai

Stephen R Pfohl

Olawale Salaudeen

Nicole Chiou

Matt Kusner

...

2024/4/18

Setting the Record Straight on Transformer Oversmoothing

arXiv preprint arXiv:2401.04301

Gbètondji JS Dovonon

Michael M Bronstein

Matt J Kusner

2024/1/9

No train no gain: Revisiting efficient training algorithms for transformer-based language models

NeurIPS 2023

Jean Kaddour

Oscar Key

Piotr Nawrot

Pasquale Minervini

Matt J Kusner

2023/7/12

Stochastic causal programming for bounding treatment effects

Kirtan Padh

Jakob Zeitler

David Watson

Matt Kusner

Ricardo Silva

...

2023/8/10

Adapting to latent subgroup shifts via concepts and proxies

Ibrahim Alabdulmohsin

Nicole Chiou

Alexander D’Amour

Arthur Gretton

Sanmi Koyejo

...

2023/4/11

DAG Learning on the Permutahedron

Valentina Zantedeschi

Luca Franceschi

Jean Kaddour

Matt Kusner

Vlad Niculae

2023

When Do Flat Minima Optimizers Work?

Jean Kaddour

Linqing Liu

Ricardo Silva

Matt Kusner

2022

Local Latent Space Bayesian Optimization over Structured Inputs

Advances in Neural Information Processing Systems

Natalie Maus

Haydn T Jones

Juston S Moore

Matt J Kusner

John Bradshaw

...

2022/1/28

Causal inference with treatment measurement error: a nonparametric instrumental variable approach

Yuchen Zhu

Limor Gultchin

Arthur Gretton

Matt J Kusner

Ricardo Silva

2022/8/17

Causal machine learning: A survey and open problems

arXiv preprint arXiv:2206.15475

Jean Kaddour

Aengus Lynch

Qi Liu

Matt J Kusner

Ricardo Silva

2022/6/30

Proximal causal learning with kernels: Two-stage estimation and moment restriction

Afsaneh Mastouri

Yuchen Zhu

Limor Gultchin

Anna Korba

Ricardo Silva

...

2021/5/10

Counterfactual data augmentation for neural machine translation

Qi Liu

Matt Kusner

Phil Blunsom

2021/6

Causal effect inference for structured treatments

Advances in Neural Information Processing Systems

Jean Kaddour

Yuchen Zhu

Qi Liu

Matt J Kusner

Ricardo Silva

2021/12/6

Unsupervised point cloud pre-training via occlusion completion

Hanchen Wang

Qi Liu

Xiangyu Yue

Joan Lasenby

Matt J Kusner

2021

MPC-friendly commitments for publicly verifiable covert security

Nitin Agrawal

James Bell

Adrià Gascón

Matt J Kusner

2021/11/12

Learning binary decision trees by argmin differentiation

Valentina Zantedeschi

Matt Kusner

Vlad Niculae

2021/7/1

Operationalizing complex causes: A pragmatic view of mediation

Limor Gultchin

David S Watson

Matt J Kusner

Ricardo Silva

2021/6/9

The long road to fairer algorithms

Nature

Matt J Kusner

Joshua R Loftus

2020/2/6

Barking up the right tree: an approach to search over molecule synthesis dags

Advances in neural information processing systems

John Bradshaw

Brooks Paige

Matt J Kusner

Marwin Segler

José Miguel Hernández-Lobato

2020

A class of algorithms for general instrumental variable models

Niki Kilbertus

Matt J Kusner

Ricardo Silva

2020/6/11

See List of Professors in Matt J. Kusner University(University College London)

Co-Authors

H-index: 87
Kilian Weinberger

Kilian Weinberger

Cornell University

H-index: 50
José Miguel Hernández-Lobato

José Miguel Hernández-Lobato

University of Cambridge

H-index: 49
Gao Huang (黄高)

Gao Huang (黄高)

Tsinghua University

H-index: 33
Roman Garnett

Roman Garnett

Washington University in St. Louis

H-index: 23
Ricardo Silva

Ricardo Silva

University College London

H-index: 22
Jacob Gardner

Jacob Gardner

University of Pennsylvania

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