115 citations · 140 across the 9 of their papers we have counts for
9 papers
MultiEarth 2023 -- Multimodal Learning for Earth and Environment Workshop and Challenge
Miriam Cha, Gregory Angelides, Mark Hamilton +6
The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2023) is the second annual CVPR workshop aimed at the monitoring and analysis of the health of Earth ecosyste…
Unsupervised Semantic Segmentation by Distilling Feature Correspondences
Mark Hamilton, Zhoutong Zhang, Bharath Hariharan +2
Unsupervised semantic segmentation aims to discover and localize semantically meaningful categories within image corpora without any form of annotation. To solve this task, algorit…
Axiomatic Explanations for Visual Search, Retrieval, and Similarity Learning
Mark Hamilton, Scott Lundberg, Lei Zhang +2
Visual search, recommendation, and contrastive similarity learning power technologies that impact billions of users worldwide. Modern model architectures can be complex and difficu…
Large-Scale Intelligent Microservices
Mark Hamilton, Nick Gonsalves, Christina Lee +8
Deploying Machine Learning (ML) algorithms within databases is a challenge due to the varied computational footprints of modern ML algorithms and the myriad of database technologie…
MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval
Mark Hamilton, Stephanie Fu, Mindren Lu +9
We introduce MosAIc, an interactive web app that allows users to find pairs of semantically related artworks that span different cultures, media, and millennia. To create this appl…
It Is Likely That Your Loss Should be a Likelihood
Mark Hamilton, Evan Shelhamer, William T. Freeman
Many common loss functions such as mean-squared-error, cross-entropy, and reconstruction loss are unnecessarily rigid. Under a probabilistic interpretation, these common losses cor…