Michael Maire

Michael Maire

University of Chicago

H-index: 36

North America-United States

About Michael Maire

Michael Maire, With an exceptional h-index of 36 and a recent h-index of 30 (since 2020), a distinguished researcher at University of Chicago, specializes in the field of Computer Vision, Deep Learning.

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

Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation

Drop-Connect as a Fault-Tolerance Approach for RRAM-based Deep Neural Network Accelerators

Residual Connections Harm Self-Supervised Abstract Feature Learning

CacheGen: Fast Context Loading for Language Model Applications

Automatic and Efficient Customization of Neural Networks for ML Applications

Deciphering'What'and'Where'Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations

Structural Adversarial Objectives for Self-Supervised Representation Learning

SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks

Michael Maire Information

University

Position

___

Citations(all)

58691

Citations(since 2020)

45559

Cited By

26037

hIndex(all)

36

hIndex(since 2020)

30

i10Index(all)

50

i10Index(since 2020)

44

Email

University Profile Page

University of Chicago

Google Scholar

View Google Scholar Profile

Michael Maire Skills & Research Interests

Computer Vision

Deep Learning

Top articles of Michael Maire

Title

Journal

Author(s)

Publication Date

Accelerated Training via Incrementally Growing Neural Networks using Variance Transfer and Learning Rate Adaptation

Advances in Neural Information Processing Systems

Xin Yuan

Pedro Savarese

Michael Maire

2024/2/13

Drop-Connect as a Fault-Tolerance Approach for RRAM-based Deep Neural Network Accelerators

arXiv preprint arXiv:2404.15498

Mingyuan Xiang

Xuhan Xie

Pedro Savarese

Xin Yuan

Michael Maire

...

2024/4/23

Residual Connections Harm Self-Supervised Abstract Feature Learning

arXiv preprint arXiv:2404.10947

Xiao Zhang

Ruoxi Jiang

William Gao

Rebecca Willett

Michael Maire

2024/4/16

CacheGen: Fast Context Loading for Language Model Applications

arXiv preprint arXiv:2310.07240

Yuhan Liu

Hanchen Li

Kuntai Du

Jiayi Yao

Yihua Cheng

...

2023/10/11

Automatic and Efficient Customization of Neural Networks for ML Applications

arXiv preprint arXiv:2310.04685

Yuhan Liu

Chengcheng Wan

Kuntai Du

Henry Hoffmann

Junchen Jiang

...

2023/10/7

Deciphering'What'and'Where'Visual Pathways from Spectral Clustering of Layer-Distributed Neural Representations

arXiv preprint arXiv:2312.06716

Xiao Zhang

David Yunis

Michael Maire

2023/12/11

Structural Adversarial Objectives for Self-Supervised Representation Learning

arXiv preprint arXiv:2310.00357

Xiao Zhang

Michael Maire

2023/9/30

SySMOL: A Hardware-software Co-design Framework for Ultra-Low and Fine-Grained Mixed-Precision Neural Networks

arXiv preprint arXiv:2311.14114

Cyrus Zhou

Vaughn Richard

Pedro Savarese

Zachary Hassman

Michael Maire

...

2023/11/23

Factorized Diffusion Architectures for Unsupervised Image Generation and Segmentation

arXiv preprint arXiv:2309.15726

Xin Yuan

Michael Maire

2023/9/27

Hyperfields: Towards zero-shot generation of nerfs from text

arXiv preprint arXiv:2310.17075

Sudarshan Babu

Richard Liu

Avery Zhou

Michael Maire

Greg Shakhnarovich

...

2023/10/26

Evaluating Machine Learning Models with NERO: Non-Equivariance Revealed on Orbits

arXiv preprint arXiv:2305.19889

Zhuokai Zhao

Takumi Matsuzawa

William Irvine

Michael Maire

Gordon L Kindlmann

2023/5/31

Run-Time Prevention of Software Integration Failures of Machine Learning APIs

Proceedings of the ACM on Programming Languages

Chengcheng Wan

Yuhan Liu

Kuntai Du

Henry Hoffmann

Junchen Jiang

...

2023/10/16

Not all bits have equal value: Heterogeneous precisions via trainable noise

Advances in Neural Information Processing Systems

Pedro Savarese

Xin Yuan

Yanjing Li

Michael Maire

2022/12/6

On convexity and linear mode connectivity in neural networks

David Yunis

Kumar Kshitij Patel

Pedro Henrique Pamplona Savarese

Gal Vardi

Jonathan Frankle

...

2022/11/23

Accelerated Training via Principled Methods for Incrementally Growing Neural Networks

Xin Yuan

Pedro Henrique Pamplona Savarese

Michael Maire

2022/9/29

Automated testing of software that uses machine learning apis

Chengcheng Wan

Shicheng Liu

Sophie Xie

Yifan Liu

Henry Hoffmann

...

2022/5/21

Boosting contrastive self-supervised learning with false negative cancellation

Tri Huynh

Simon Kornblith

Matthew R Walter

Michael Maire

Maryam Khademi

2022

Domain-independent dominance of adaptive methods

Pedro Savarese

David McAllester

Sudarshan Babu

Michael Maire

2021

Online meta-learning via learning with layer-distributed memory

Advances in Neural Information Processing Systems

Sudarshan Babu

Pedro Savarese

Michael Maire

2021/12/6

A replication of are machine learning cloud APIs used correctly

Chengcheng Wan

Shicheng Liu

Henry Hoffmann

Michael Maire

Shan Lu

2021/5/25

See List of Professors in Michael Maire University(University of Chicago)