Browsing: ML News

Fine-tuning pre-trained models has become the basis for achieving state-of-the-art results across various tasks in machine learning. This practice involves adjusting a model, initially trained on…

Solving partial differential equations (PDEs) is complex, just like the events they explain. These equations help determine how things change over space and time, and they’re…

In 2024, the landscape of Python libraries for machine learning and deep learning continues to evolve, integrating more advanced features and offering more efficient and easier…

Large Language Models (LLMs) are central to modern artificial intelligence applications, providing the computational intellect required to understand and generate human-like text. These models have been…

GoogleAI researchers released AutoBNN to address the challenge of effectively modeling time series data for forecasting purposes. Traditional Bayesian approaches like Gaussian processes (GPs) and structural…

In the field of Artificial Intelligence (AI), Multi-Layer Perceptrons (MLPs) are the foundation for many Machine Learning (ML) tasks, including partial differential equation solving, density function…

Deep Neural Networks (DNNs) demonstrated tremendous improvement in numerous difficult activities, matching or even outperforming human ability. As a result of this accomplishment, DNNs were widely…

In today’s world, where data is distributed across various locations and privacy is paramount, Federated Learning (FL) has emerged as a game-changing solution. It enables multiple…

With the recent advancements in the field of Machine Learning (ML), Reinforcement Learning (RL), which is one of its branches, has become significantly popular. In RL,…

In machine learning, one method that has consistently demonstrated its worth across various applications is the Support Vector Machine (SVM). Known for its adeptness at parsing…