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Found 7 papers, 4 papers with code
Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing
We introduce Llamba, a family of efficient recurrent language models distilled from Llama-3. x into the Mamba architecture.
Prospector Heads: Generalized Feature Attribution for Large Models & Data
Feature attribution, the ability to localize regions of the input data that are relevant for classification, is an important capability for ML models in scientific and biomedical domains.
Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography
Extracting quantitative body composition measures manually from CT scans is a cumbersome and time-consuming task.
Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation
Purpose: To present and evaluate Dafne (deep anatomical federated network), a freely available decentralized, collaborative deep learning system for the semantic segmentation of radiological images through federated incremental learning.
Monarch: Expressive Structured Matrices for Efficient and Accurate Training
To address these issues, we propose a class of matrices (Monarch) that is hardware-efficient (they are parameterized as products of two block-diagonal matrices for better hardware utilization) and expressive (they can represent many commonly used transforms).
Using Computer Vision to Automate Hand Detection and Tracking of Surgeon Movements in Videos of Open Surgery
A state-of-the-art convolutional neural network architecture for object detection was used to detect operating hands in open surgery videos.
