Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...

Abstract: In the last decade, the rapid development of deep learning (DL) has made it possible to perform automatic, accurate, and robust Change Detection (CD) on large volumes of Remote Sensing ...

Dive deep into Nesterov Accelerated Gradient (NAG) and learn how to implement it from scratch in Python. Perfect for ...

Build the AdamW optimizer from scratch in Python. Learn how it improves training stability and generalization in deep ...

Landscaper is available on PyPI, making it easy to install and integrate into your projects. @misc{https://doi.org/10.5281/zenodo.15874987, doi = {10.5281/ZENODO ...

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 ...

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 ...

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 ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

If there is one skill that sits at the heart of most successful AI and machine learning projects today, it is Python. Whether a company wants to build smarter automation, design predictive solutions, ...