16 papers
Mol-JEPA: A multimodal Joint Embedding Predictive Architecture for Molecules
Florian Rottach, Sebastian Schieferdecker, William Rudman +2
Despite recent advances in molecular foundation models, several limitations remain, such as chemically invalid augmentations, modality collapse, and incomplete representation of bi…
Self-supervised DXA representations encode multi-system disease risk, biological aging and heritability
Gil Sasson, Zachary Levine, Smadar Shilo +9
Whole-body dual-energy X-ray absorptiometry (DXA) scans are routinely acquired to measure bone density and regional body composition, leaving their spatial structure largely unused…
VideoGPA: Distilling Geometry Priors for 3D-Consistent Video Generation
Hongyang Du, Junjie Ye, Xiaoyan Cong +7
While recent video diffusion models (VDMs) produce visually impressive results, they fundamentally struggle to maintain 3D structural consistency, often resulting in object deforma…
Rectified LpJEPA: Joint-Embedding Predictive Architectures with Sparse and Maximum-Entropy Representations
Yilun Kuang, Yash Dagade, Tim G. J. Rudner +2
Joint-Embedding Predictive Architectures (JEPA) learn view-invariant representations and admit projection-based distribution matching for collapse prevention. Existing approaches r…
A Lightweight Library for Energy-Based Joint-Embedding Predictive Architectures
Basile Terver, Randall Balestriero, Megi Dervishi +8
We present EB-JEPA, an open-source library for learning representations and world models using Joint-Embedding Predictive Architectures (JEPAs). JEPAs learn to predict in represent…
Semantic Tube Prediction: Beating LLM Data Efficiency with JEPA
Hai Huang, Yann LeCun, Randall Balestriero
Large Language Models (LLMs) obey consistent scaling laws -- empirical power-law fits that predict how loss decreases with compute, data, and parameters. While predictive, these la…