FAIME: An Object-Oriented Methodology for Application Plug-and-Play. - Bill Chu; Junsheng Long; Michael Matthews; J. G. Barnes; J. Sims; Mark Hamilton; Russ Lambert (J. Object Oriented Program., 1998)

FPGA Implementation of an Elliptic Curve Processor Using the GLV Method. - Mark Hamilton; William P. Marnane (ReConFig, 2009)

FPGA Implementations of SHA-3 Candidates: CubeHash, Grøstl, Lane, Shabal and Spectral Hash. - Brian Baldwin; Andrew Byrne; Mark Hamilton; Neil Hanley; Robert P. McEvoy; Weibo Pan; William P. Marnane (IACR Cryptol. ePrint Arch., 2009)

FPGA Implementations of the Round Two SHA-3 Candidates. - Brian Baldwin; Andrew Byrne; Liang Lu; Mark Hamilton; Neil Hanley; Máire O'Neill; William P. Marnane (FPL, 2010)

A Hardware Wrapper for the SHA-3 Hash Algorithms. - Brian Baldwin; Andrew Byrne; Liang Lu; Mark Hamilton; Neil Hanley; Máire O'Neill; William P. Marnane (IACR Cryptol. ePrint Arch., 2010)

A Comparison on FPGA of Modular Multipliers Suitable for Elliptic Curve Cryptography over GF(p) for Specific p Values. - Mark Hamilton; William P. Marnane; Arnaud Tisserand (FPL, 2011)

Co-Z ECC scalar multiplications for hardware, software and hardware-software co-design on embedded systems. - Brian Baldwin; Raveen R. Goundar; Mark Hamilton; William P. Marnane (J. Cryptogr. Eng., 2012)

Implementation of a secure TLS coprocessor on an FPGA. - Mark Hamilton; William P. Marnane (Microprocess. Microsystems, 2016)

Preliminary assessment of the uses of sensors and the spectral properties of weed and native species: In Kosciusko National Park, NSW, Australia. - Chad Ajamian; Hsing-Chung Chang; Kerrie Tomkins; Hillary Cherry; Mark Hamilton (ICST, 2017)

Flexible and Scalable Deep Learning with MMLSpark. - Mark Hamilton; Sudarshan Raghunathan; Akshaya Annavajhala; Danil Kirsanov; Eduardo de Leon; Eli Barzilay; Ilya Matiach; Joe Davison; Maureen Busch; Miruna Oprescu; Ratan Sur; Roope Astala; et al. (PAPIs, 2017)

SPOT Poachers in Action: Augmenting Conservation Drones With Automatic Detection in Near Real Time. - Elizabeth Bondi; Fei Fang 001; Mark Hamilton; Debarun Kar; Donnabell Dmello; Jongmoo Choi; Robert Hannaford; Arvind Iyer; Lucas Joppa; Milind Tambe; Ram Nevatia (AAAI, 2018)

MMLSpark: Unifying Machine Learning Ecosystems at Massive Scales. - Mark Hamilton; Sudarshan Raghunathan; Ilya Matiach; Andrew Schonhoffer; Anand Raman; Eli Barzilay; Minsoo Thigpen; Karthik Rajendran; Janhavi Suresh Mahajan; Courtney Cochrane; Abhiram Eswaran; Ari Green (CoRR, 2018)

Semi-Supervised Translation with MMD Networks. - Mark Hamilton (CoRR, 2018)

Large-Scale Intelligent Microservices. - Mark Hamilton; Nick Gonsalves; Christina Lee; Anand Raman; Brendan Walsh; Siddhartha Prasad; Dalitso Banda; Lucy Zhang; Lei Zhang 001; William T. Freeman (IEEE BigData, 2020)

MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval. - Mark Hamilton; Stephanie Fu; Mindren Lu; Johnny Bui; Darius Bopp; Zhenbang Chen; Felix Tran; Margaret Wang; Marina Rogers; Lei Zhang 001; Chris Hoder; William T. Freeman (NeurIPS (Competition and Demos), 2020)

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

Conditional Image Retrieval. - Mark Hamilton; Stephanie Fu; William T. Freeman; Mindren Lu (CoRR, 2020)

Model-Agnostic Explainability for Visual Search. - Mark Hamilton; Scott M. Lundberg; Lei Zhang 001; Stephanie Fu; William T. Freeman (CoRR, 2021)

Axiomatic Explanations for Visual Search, Retrieval, and Similarity Learning. - Mark Hamilton; Scott M. Lundberg; Stephanie Fu; Lei Zhang 001; William T. Freeman (ICLR, 2022)

Unsupervised Semantic Segmentation by Distilling Feature Correspondences. - Mark Hamilton; Zhoutong Zhang; Bharath Hariharan; Noah Snavely; William T. Freeman (ICLR, 2022)

Remote Tiny Weeds Detection. - Lihong Zheng; D. M. Motiur Rahaman; Mark Hamilton; Remy L. Dehaan; Felipe Gonzalez; Jane E. Kelly; Hillary Cherry (PSIVT, 2022)

MultiEarth 2022 - Multimodal Learning for Earth and Environment Workshop and Challenge. - Miriam Cha; Kuan Wei Huang; Morgan Schmidt; Gregory Angelides; Mark Hamilton; Sam Goldberg; Armando Cabrera; Phillip Isola; Taylor Perron; Bill Freeman; Yen-Chen Lin; Brandon Swenson; et al. (CoRR, 2022)

Developing a Series of AI Challenges for the United States Department of the Air Force. - Vijay Gadepally; Gregory Angelides; Andrei Barbu; Andrew Bowne; Laura J. Brattain; Tamara Broderick; Armando Cabrera; Glenn Carl; Ronisha Carter; Miriam Cha; Emilie Cowen; Jesse Cummings; et al. (CoRR, 2022)

StatTexNet: Evaluating the Importance of Statistical Parameters for Pyramid-Based Texture and Peripheral Vision Models. - Christian Koevesdi; Vasha DuTell; Anne Harrington; Mark Hamilton; William T. Freeman; Ruth Rosenholtz (Gaze Meets ML, 2023)

Exploring perceptual straightness in learned visual representations. - Anne Harrington; Vasha DuTell; Ayush Tewari; Mark Hamilton; Simon Stent; Ruth Rosenholtz; William T. Freeman (ICLR, 2023)

Large-Scale Automatic Audiobook Creation. - Brendan Walsh; Mark Hamilton; Greg Newby; Xi Wang 016; Serena Ruan; Sheng Zhao; Lei He 005; Shaofei Zhang; Eric Dettinger; William T. Freeman; Markus Weimer (INTERSPEECH, 2023)

Exploring Gender and Race Biases in the NFT Market. - Howard Zhong; Mark Hamilton (CoRR, 2023)

MultiEarth 2023 - Multimodal Learning for Earth and Environment Workshop and Challenge. - Miriam Cha; Gregory Angelides; Mark Hamilton; Andy Soszynski; Brandon Swenson; Nathaniel Maidel; Phillip Isola; Taylor Perron; Bill Freeman (CoRR, 2023)

Autonomous Detection of Mouse-Ear Hawkweed Using Drones, Multispectral Imagery and Supervised Machine Learning. - Amarasingam Narmilan; Mark Hamilton; Jane E. Kelly; Lihong Zheng; Juan Sandino; Felipe Gonzalez; Remy L. Dehaan; Hillary Cherry (Remote. Sens., 2023)

Separating the "Chirp" from the "Chat": Self-supervised Visual Grounding of Sound and Language. - Mark Hamilton; Andrew Zisserman; John R. Hershey; William T. Freeman (CVPR, 2024)

Seeing Faces in Things: A Model and Dataset for Pareidolia. - Mark Hamilton; Simon Stent; Vasha DuTell; Anne Harrington; Jennifer Corbett; Ruth Rosenholtz; William T. Freeman (ECCV (65), 2024)

FeatUp: A Model-Agnostic Framework for Features at Any Resolution. - Stephanie Fu; Mark Hamilton; Laura E. Brandt; Axel Feldmann; Zhoutong Zhang; William T. Freeman (ICLR, 2024)

COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery. - Anne Harrington; Vasha DuTell; Mark Hamilton; Ayush Tewari; Simon Stent; William T. Freeman; Ruth Rosenholtz (ICLR, 2024)

I-Con: A Unifying Framework for Representation Learning. - Shaden Naif Alshammari; John R. Hershey; Axel Feldmann; William T. Freeman; Mark Hamilton (ICLR, 2025)