Caffe: Convolutional Architecture for Fast Feature Embedding. - Yangqing Jia; Evan Shelhamer; Jeff Donahue; Sergey Karayev; Jonathan Long; Ross B. Girshick; Sergio Guadarrama; Trevor Darrell (ACM Multimedia, 2014)

cuDNN: Efficient Primitives for Deep Learning. - Sharan Chetlur; Cliff Woolley; Philippe Vandermersch; Jonathan Cohen; John Tran; Bryan Catanzaro; Evan Shelhamer (CoRR, 2014)

Scene Intrinsics and Depth from a Single Image. - Evan Shelhamer; Jonathan T. Barron; Trevor Darrell (ICCV Workshops, 2015)

Fully Convolutional Multi-Class Multiple Instance Learning. - Deepak Pathak; Evan Shelhamer; Jonathan Long; Trevor Darrell (ICLR (Workshop), 2015)

Fine-grained pose prediction, normalization, and recognition. - Ning Zhang 014; Evan Shelhamer; Yang Gao 029; Trevor Darrell (CoRR, 2015)

Clockwork Convnets for Video Semantic Segmentation. - Evan Shelhamer; Kate Rakelly; Judy Hoffman; Trevor Darrell (ECCV Workshops (3), 2016)

Loss is its own Reward: Self-Supervision for Reinforcement Learning. - Evan Shelhamer; Parsa Mahmoudieh; Max Argus; Trevor Darrell (ICLR (Workshop), 2017)

Fully Convolutional Networks for Semantic Segmentation. - Evan Shelhamer; Jonathan Long; Trevor Darrell (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Zero-Shot Visual Imitation. - Deepak Pathak; Parsa Mahmoudieh; Guanghao Luo; Pulkit Agrawal 001; Dian Chen 001; Yide Shentu; Evan Shelhamer; Jitendra Malik; Alexei A. Efros; Trevor Darrell (CVPR Workshops, 2018)

Deep Layer Aggregation. - Fisher Yu 001; Dequan Wang; Evan Shelhamer; Trevor Darrell (CVPR, 2018)

Conditional Networks for Few-Shot Semantic Segmentation. - Kate Rakelly; Evan Shelhamer; Trevor Darrell; Alyosha A. Efros; Sergey Levine (ICLR (Workshop), 2018)

Learning Rich Image Representation with Deep Layer Aggregation. - Fisher Yu 001; Dequan Wang; Evan Shelhamer; Trevor Darrell (ICLR (Workshop), 2018)

Few-Shot Segmentation Propagation with Guided Networks. - Kate Rakelly; Evan Shelhamer; Trevor Darrell; Alexei A. Efros; Sergey Levine (CoRR, 2018)

Infinite Mixture Prototypes for Few-shot Learning. - Kelsey R. Allen; Evan Shelhamer; Hanul Shin; Joshua B. Tenenbaum (ICML, 2019)

Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields. - Evan Shelhamer; Dequan Wang; Trevor Darrell (CoRR, 2019)

Dynamic Scale Inference by Entropy Minimization. - Dequan Wang; Evan Shelhamer; Bruno A. Olshausen; Trevor Darrell (CoRR, 2019)

Fully Test-time Adaptation by Entropy Minimization. - Dequan Wang; Evan Shelhamer; Shaoteng Liu; Bruno A. Olshausen; Trevor Darrell (CoRR, 2020)

It Is Likely That Your Loss Should be a Likelihood. - Mark Hamilton; Evan Shelhamer; William T. Freeman (CoRR, 2020)

Tent: Fully Test-Time Adaptation by Entropy Minimization. - Dequan Wang; Evan Shelhamer; Shaoteng Liu; Bruno A. Olshausen; Trevor Darrell (ICLR, 2021)

Confidence Adaptive Anytime Pixel-Level Recognition. - Zhuang Liu 003; Trevor Darrell; Evan Shelhamer (CoRR, 2021)

Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks. - Dequan Wang; An Ju; Evan Shelhamer; David A. Wagner 001; Trevor Darrell (CoRR, 2021)

On-target Adaptation. - Dequan Wang; Shaoteng Liu; Sayna Ebrahimi; Evan Shelhamer; Trevor Darrell (CoRR, 2021)

Object Discovery and Representation Networks. - Olivier J. Hénaff; Skanda Koppula; Evan Shelhamer; Daniel Zoran; Andrew Jaegle; Andrew Zisserman; João Carreira 001; Relja Arandjelovic (ECCV (27), 2022)

Anytime Dense Prediction with Confidence Adaptivity. - Zhuang Liu 003; Zhiqiu Xu; Hung-Ju Wang; Trevor Darrell; Evan Shelhamer (ICLR, 2022)

Perceiver IO: A General Architecture for Structured Inputs & Outputs. - Andrew Jaegle; Sebastian Borgeaud; Jean-Baptiste Alayrac; Carl Doersch; Catalin Ionescu; David Ding; Skanda Koppula; Daniel Zoran; Andrew Brock; Evan Shelhamer; Olivier J. Hénaff; Matthew M. Botvinick; et al. (ICLR, 2022)

Evaluating the Adversarial Robustness of Adaptive Test-time Defenses. - Francesco Croce; Sven Gowal; Thomas Brunner; Evan Shelhamer; Matthias Hein 001; A. Taylan Cemgil (ICML, 2022)

Hierarchical Perceiver. - João Carreira 001; Skanda Koppula; Daniel Zoran; Adrià Recasens; Catalin Ionescu; Olivier J. Hénaff; Evan Shelhamer; Relja Arandjelovic; Matthew M. Botvinick; Oriol Vinyals; Karen Simonyan; Andrew Zisserman; et al. (CoRR, 2022)

Back to the Source: Diffusion-Driven Test-Time Adaptation. - Jin Gao; Jialing Zhang; Xihui Liu; Trevor Darrell; Evan Shelhamer; Dequan Wang (CoRR, 2022)

Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods. - Skanda Koppula; Yazhe Li; Evan Shelhamer; Andrew Jaegle; Nikhil Parthasarathy; Relja Arandjelovic; João Carreira 001; Olivier J. Hénaff (CoRR, 2022)

Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts. - Francesco Croce; Sylvestre-Alvise Rebuffi; Evan Shelhamer; Sven Gowal (CVPR, 2023)

Back to the Source: Diffusion-Driven Adaptation to Test-Time Corruption. - Jin Gao; Jialing Zhang; Xihui Liu; Trevor Darrell; Evan Shelhamer; Dequan Wang (CVPR, 2023)

Exploring Simple and Transferable Recognition-Aware Image Processing. - Zhuang Liu 003; Hung-Ju Wang; Tinghui Zhou; Zhiqiang Shen; Bingyi Kang; Evan Shelhamer; Trevor Darrell (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences. - Saiyue Lyu; Shadab Shaikh; Frederick Shpilevskiy; Evan Shelhamer; Mathias Lécuyer (NeurIPS, 2024)

Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples. - Saiyue Lyu; Shadab Shaikh; Frederick Shpilevskiy; Evan Shelhamer; Mathias Lécuyer (CoRR, 2024)

Galileo: Learning Global and Local Features in Pretrained Remote Sensing Models. - Gabriel Tseng; Anthony Fuller; Marlena Reil; Henry Herzog; Patrick Beukema; Favyen Bastani; James R. Green; Evan Shelhamer; Hannah Kerner; David Rolnick (CoRR, 2025)

Simpler Fast Vision Transformers with a Jumbo CLS Token. - Anthony Fuller; Yousef Yassin; Daniel G. Kyrollos; Evan Shelhamer; James R. Green (CoRR, 2025)

ReservoirTTA: Prolonged Test-time Adaptation for Evolving and Recurring Domains. - Guillaume Vray; Devavrat Tomar; Xufeng Gao; Jean-Philippe Thiran; Evan Shelhamer; Behzad Bozorgtabar (CoRR, 2025)

LookWhere? Efficient Visual Recognition by Learning Where to Look and What to See from Self-Supervision. - Anthony Fuller; Yousef Yassin; Junfeng Wen; Daniel G. Kyrollos; Tarek Ibrahim; James R. Green; Evan Shelhamer (CoRR, 2025)

Asymmetric Duos: Sidekicks Improve Uncertainty. - Tim G. Zhou; Evan Shelhamer; Geoff Pleiss (CoRR, 2025)

AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data. - Christopher F. Brown; Michal Kazmierski; Valerie Pasquarella; William Rucklidge; Masha Samsikova; Chenhui Zhang; Evan Shelhamer; Estefania Lahera; Olivia Wiles; Simon Ilyushchenko; Noel Gorelick; Lihui Lydia Zhang; et al. (CoRR, 2025)