Locally linear embedding (LLE)
Locally Linear Embedding (LLE) is a nonlinear dimensionality reduction technique used for data visualization and analysis in machine learning.
Artificial Intelligence
Bayesian network
A Bayesian network is a graphical model that represents probabilistic relationships among variables using directed acyclic graphs.
Uniform manifold approximation and projection (UMAP)
Uniform manifold approximation and projection (UMAP) is a dimension reduction technique used in data science for visualizing and interpreting high-dimensional data. It is known for preserving both local and global data structure, making it valuable for exploratory data analysis and machine learning.
CLIP (neural network)
CLIP (Contrastive Language–Image Pre-training) is a neural network model developed by OpenAI that connects text and images by learning visual concepts from natural language descriptions. It enables zero-shot classification and understanding of images based on textual input.
CIFAR-10
CIFAR-10 is a widely used dataset in machine learning for image classification, consisting of 60,000 32×32 color images in 10 different classes.
Mila (institute)
Mila is a research institute specializing in artificial intelligence based in Montreal, Canada. It focuses on machine learning and deep learning research and collaborates with academic and industry partners worldwide.
SantaCoder
SantaCoder is an open-source large language model designed for code generation and programming assistance. It is aimed at facilitating software development through AI-driven code completion and generation.
Latent diffusion model (LDM)
A latent diffusion model (LDM) is a type of generative machine learning model that performs diffusion processes in a compressed latent space, enabling efficient and high-quality image synthesis and related tasks. By operating in a lower-dimensional representation, LDMs reduce computational costs while maintaining detailed output.
GPT-2
GPT-2 is an advanced language processing AI developed by OpenAI, known for its ability to generate human-like text based on given prompts.
UNESCO Recommendation on AI Ethics
The UNESCO Recommendation on AI Ethics is an international framework adopted to guide the ethical development and deployment of artificial intelligence technologies. It emphasizes human rights, transparency, fairness, and accountability in AI systems.