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Found 5 papers, 1 papers with code
AviationGPT: A Large Language Model for the Aviation Domain
The advent of ChatGPT and GPT-4 has captivated the world with large language models (LLMs), demonstrating exceptional performance in question-answering, summarization, and content generation.
Adapting Sentence Transformers for the Aviation Domain
Learning effective sentence representations is crucial for many Natural Language Processing (NLP) tasks, including semantic search, semantic textual similarity (STS), and clustering.
Multi-Airport Delay Prediction with Transformers
Traffic, demand, weather, and traffic management actions are all critical inputs to any prediction model.
Generated Loss and Augmented Training of MNIST VAE
The variational autoencoder (VAE) framework is a popular option for training unsupervised generative models, featuring ease of training and latent representation of data.
Generated Loss, Augmented Training, and Multiscale VAE
The variational autoencoder (VAE) framework remains a popular option for training unsupervised generative models, especially for discrete data where generative adversarial networks (GANs) require workaround to create gradient for the generator.
