Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

A new computational model of the brain based closely on its biology and physiology has not only learned a simple visual ...

These days, large language models can handle increasingly complex tasks, writing complex code and engaging in sophisticated ...

The current boom in AI technology has ridden on a wave known as ‘deep learning’, which is an approach to creating intelligent ...

Overview:  Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...

Abstract: This paper introduces a novel structure for deep Gaussian processes (DGPs) and a method for determining their depths. The proposed framework enables faster convergence of their parameters ...

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: The leaf area index (LAI) serves as a significant vegetation growth indicator and plays an essential role in vegetation’s feedback to climate change. Currently, artificial intelligence (e.g.

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

With the growing model size of deep neural networks (DNN), deep learning training is increasingly relying on handcrafted search spaces to find efficient parallelization execution plans. However, our ...