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Jeffrey Gu

7 accepted papers

2026

CryoHype: Reconstructing a thousand cryo-EM structures with transformer-based hypernetworks

CVPR 2026

Cryo-electron microscopy (cryo-EM) is an indispensable technique for determining the 3D structures of dynamic biomolecular complexes. While typically applied to image a single molecular species, cryo-EM holds great potential for structure determination of many targets simultaneously in a high-throug

Cited by 0SourceScholar
2025

BIOMEDICA: An Open Biomedical Image-Caption Archive, Dataset, and Vision-Language Models Derived from Scientific Literature

CVPR 2025poster

The development of vision-language models (VLMs) is driven by large-scale and diverse multi-modal datasets. However, progress toward generalist biomedical VLMs is limited by the lack of annotated, publicly accessible datasets across biology and medicine. Existing efforts are limited to narrow domain…

2025

Foundation Models Secretly Understand Neural Network Weights: Enhancing Hypernetwork Architectures with Foundation Models

ICLR 2025poster

Large pre-trained models, or foundation models, have shown impressive performance when adapted to a variety of downstream tasks, often out-performing specialized models. Hypernetworks, neural networks that generate some or all of the parameters of another neural network, have become an increasingly…

Cited by 0SourcePDFScholar
2023

NeMo: Learning 3D Neural Motion Fields From Multiple Video Instances of the Same Action

CVPR 2023highlight

The task of reconstructing 3D human motion has wide-ranging applications. The gold standard Motion capture (MoCap) systems are accurate but inaccessible to the general public due to their cost, hardware, and space constraints. In contrast, monocular human mesh recovery (HMR) methods are much more ac…

Cited by 9SourcePDFScholar
2021

Capturing implicit hierarchical structure in 3D biomedical images with self-supervised hyperbolic representations

NeurIPS 2021poster

We consider the task of representation learning for unsupervised segmentation of 3D voxel-grid biomedical images. We show that models that capture implicit hierarchical relationships between subvolumes are better suited for this task. To that end, we consider encoder-decoder architectures with a hyp…

Cited by 35SourcePDFScholar