16.2k citations · 16.3k across the 5 of their papers we have counts for
6 papers
C-lisp and Flexible Macro Programming with S-expressions
Vedanth Padmaraman, Sasank Chilamkurthy
Llamalisp is a compiler framework intended to target offload processor backends such as GPUs, using intermediate representation languages (IRs) that are device-agnostic. The Lla…
One-Step Diffusion Distillation via Deep Equilibrium Models
Zhengyang Geng, Ashwini Pokle, J. Zico Kolter
Diffusion models excel at producing high-quality samples but naively require hundreds of iterations, prompting multiple attempts to distill the generation process into a faster net…
Deep-ASPECTS: A Segmentation-Assisted Model for Stroke Severity Measurement
Ujjwal Upadhyay, Mukul Ranjan, Satish Golla +5
A stroke occurs when an artery in the brain ruptures and bleeds or when the blood supply to the brain is cut off. Blood and oxygen cannot reach the brain's tissues due to the ruptu…
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa +18
Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible…
Development and Validation of Deep Learning Algorithms for Detection of Critical Findings in Head CT Scans
Sasank Chilamkurthy, Rohit Ghosh, Swetha Tanamala +6
Importance: Non-contrast head CT scan is the current standard for initial imaging of patients with head trauma or stroke symptoms. Objective: To develop and validate a set of deep…
2D-3D Fully Convolutional Neural Networks for Cardiac MR Segmentation
Jay Patravali, Shubham Jain, Sasank Chilamkurthy
In this paper, we develop a 2D and 3D segmentation pipelines for fully automated cardiac MR image segmentation using Deep Convolutional Neural Networks (CNN). Our models are traine…