6 citations · 7 across the 3 of their papers we have counts for
5 papers
KneePreM: Towards 3D Knee MRI Foundation Models via Large-Scale Unlabeled Pretraining and Label-Efficient Fine-Tuning
Xinxin Wang, Liam Hazan, Jing Li +3
Background: Large volumes of unlabeled knee MRI scans are available across repositories but remain insufficiently leveraged. We developed KneePreM, a knee-specific 3D self-supervis…
MAMMAL -- Molecular Aligned Multi-Modal Architecture and Language
Yoel Shoshan, Moshiko Raboh, Michal Ozery-Flato +18
Large language models applied to vast biological datasets have the potential to transform biology by uncovering disease mechanisms and accelerating drug development. However, curre…
A large dataset curation and benchmark for drug target interaction
Alex Golts, Vadim Ratner, Yoel Shoshan +7
Bioactivity data plays a key role in drug discovery and repurposing. The resource-demanding nature of \textit{in vitro} and \textit{in vivo} experiments, as well as the recent adva…
BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
BigScience Workshop, :, Teven Le Scao +391
Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to wi…
Length Learning for Planar Euclidean Curves
Barak Or, Liam Hazan
In this work, we used deep neural networks (DNNs) to solve a fundamental problem in differential geometry. One can find many closed-form expressions for calculating curvature, leng…