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- Generative Pre-trained Transformer Description: Generative Pre-trained Transformers (GPT) are a type of transformer model that is pre-trained on a large corpus of text and(...) Read more
- Geometric Deep Learning Description: Geometric deep learning is a field that extends deep learning methods to non-Euclidean domains such as graphs and manifolds. Unlike(...) Read more
- Graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. Description: Graph theory is the study of graphs, which are mathematical structures used to model pairwise relationships between objects. A(...) Read more
- Generalized Regression Neural Network Description: A generalized regression neural network is a type of neural network used for regression analysis and can model complex(...) Read more
- Geometric Probability Description: Geometric probability is a branch of probability theory that deals with the probability of geometric outcomes. It focuses on(...) Read more
- Graph Representation Learning Description: Graph representation learning is a method for learning the representation of nodes and edges in a graph to enhance various(...) Read more
- Graph Convolutional Network Description: A Graph Convolutional Network (GCN) is a type of neural network that operates directly on graphs, allowing the processing of data(...) Read more
- Graph Neural Network Description: A Graph Neural Network (GNN) is a type of neural network designed to operate on graph structures, making it particularly useful for(...) Read more
- Gradient Clipping Description: Gradient clipping is a technique used in training neural networks to prevent the problem of exploding gradients, which can occur(...) Read more
- Gradient Descent with Momentum Description: Momentum gradient descent is an optimization technique that enhances the standard gradient descent algorithm by incorporating a(...) Read more
- Gradient Boosted Trees Description: Gradient boosting trees are an ensemble learning technique that builds models in a staged manner using decision trees as base(...) Read more
- Gradient-Based Optimization Description: Gradient-based optimization is an optimization method that uses the gradient of the objective function to find the minimum or(...) Read more
- Gaussian Naive Bayes Description: Gaussian naive Bayes is a variant of the naive Bayes algorithm used in machine learning and statistics. This model assumes that(...) Read more
- Gravitational Search Algorithm Description: The Gravitational Search Algorithm is a nature-inspired optimization method based on the law of gravity and mass interactions. This(...) Read more
- Gaussian Description: The Gaussian distribution, also known as the normal distribution, is a probability function that describes how the values of a(...) Read more
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