IEEE

ISACPP: Interference-Aware Scheduling Approach for Deep Learning Training Workloads Based on Co-Location Performance Prediction

Abstract: Traditional exclusive cloud resource allocation for deep learning training (DLT) workloads is unsuitable for advanced GPU infrastructure, leading to resource under-utilization. Fortunately, ...
Deep Learning with Yacine on MSN

Adam optimizer from scratch in Python – step-by-step tutorial

Learn how to build the Adam optimizer from scratch in Python. Perfect for beginners who want to understand how modern ...
Deep Learning with Yacine on MSN

Digit recognition with deep learning — PyTorch beginner project

Learn how to build a digit recognition model from scratch using PyTorch! This beginner-friendly deep learning project walks ...
GitHub

$\infty$-Video: A Training-Free Approach to Long Video Understanding via Continuous-Time Memory Consolidation

Official implementation of the paper $\infty$-Video: A Training-Free Approach to Long Video Understanding via Continuous-Time Memory Consolidation. **Abstract**: *Current video-language models ...
eLife

Separating selection from mutation in antibody language models

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
IEEE

Cardiac Output Quantification via Esophageal Photoplethysmography and Deep Learning

Abstract: Continuous minimally invasive cardiac output (CO) measurement via photoplethysmography (PPG) has received much attention in daily monitoring. However, the precision of current research is ...
GitHub

TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling" (ICLR 2025)

This is the official repository of the paper "TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling". It consists of two parts: One dot represents a performance score on one ...