#deep-learning
Adversarial attacks on machine learning models are becoming increasingly prevalent and pose a significant threat to the safety and privacy of users.... Read more
Yes, there have been several approaches developed for combining multiple modalities in models. One popular approach is multi-modal learning, which... Read more
Activation functions are an essential component of deep learning models, as they introduce non-linearity to the model's output, which allows for the... Read more
Graph neural networks (GNNs) have gained significant attention in recent years due to their ability to model complex systems represented as graphs.... Read more
Artificial Intelligence (AI) refers to the ability of machines to learn and perform tasks that typically require human intelligence, such as... Read more
Artificial Intelligence (AI) has been a hot topic in the world of technology and science for many years now. The question of whether or not we can... Read more
Transfer learning is a machine learning technique that enables the use of a pre-trained model on a new, related task. This approach has become... Read more
As an AI language model, I do not have the ability to explore or research new deep learning architectures. However, there have been many new... Read more
Adversarial attacks on machine learning models are a growing concern, as they can be used to undermine the accuracy and reliability of these models.... Read more
Artificial intelligence (AI) has made remarkable progress in recent years, thanks to the emergence of powerful computing hardware and sophisticated... Read more