Deep Learning with Yacine on MSN

Adadelta optimizer explained – Python tutorial for beginners & pros

Learn how to implement the Adadelta optimization algorithm from scratch in Python. This tutorial explains the math behind ...
Deep Learning with Yacine on MSN

Nadam optimizer explained: Python tutorial for beginners & pros

Learn how to implement the Nadam optimizer from scratch in Python. This tutorial walks you through the math behind Nadam, ...
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 ...

Vibrant’s New Title Empowers Emerging Developers With the Foundations of Efficient, Real-World Programming

Author Shawn Peters blends clarity and rigor to make data structures and algorithms accessible to all learners. COLORADO, CO, UNITED STATES, January 2, 2026 /EINPresswire.com/ — Vibrant Publishers ...
GitHub

Learn PyTorch for Deep Learning

00 - PyTorch Fundamentals Many fundamental PyTorch operations used for deep learning and neural networks. Go to exercises & extra-curriculum Go to slides 01 - PyTorch Workflow Provides an outline for ...
TechAnnouncer

Mastering AI Training Courses: Your Guide to Top Programs in 2026

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to language for AI because it’s relatively easy to learn and has a massive library of ...
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 ...
IEEE

Backdoor Attack and Defense on Deep Learning: A Survey

Abstract: Deep learning, as an important branch of machine learning, has been widely applied in computer vision, natural language processing, speech recognition, and more. However, recent studies have ...
Microsoft

Accurate and scalable exchange-correlation with deep learning

Density Functional Theory (DFT) is the most widely used electronic structure method for predicting the properties of molecules and materials. Although DFT is, in principle, an exact reformulation of ...
Smithsonian Magazine

Deep-Sea Mining Test in the Pacific Drastically Reduced Biodiversity and Animal Populations

The study inventoried thousands of mollusks, worms, crustaceans and other small marine creatures. Natural History Museum, London and University of Gothenburg As demand soars for critical minerals for ...
IEEE

Deep Learning for Inertial Positioning: A Survey

Abstract: Inertial sensors are widely utilized in smartphones, drones, vehicles, and wearable devices, playing a crucial role in enabling ubiquitous and reliable localization. Inertial sensor-based ...