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- Graft-versus-host disease Description: Graft-versus-host disease (GVHD) is a complication that can arise after a stem cell or organ transplant, where the immune cells(...) Read more
- Glycolytic Description: The term 'glycolytic' refers to processes and metabolic pathways involving glycolysis, a set of biochemical reactions that break(...) Read more
- Generative Adversarial Networks Description: Generative Adversarial Networks (GANs) are a class of machine learning frameworks where two neural networks compete against each(...) Read more
- Goal-Oriented Learning Description: Goal-oriented learning is an educational approach that focuses on achieving specific goals through the implementation of various(...) Read more
- Generative Model Description: A generative model is a type of statistical model that generates new data points from the learned distribution of training data.(...) Read more
- 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
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