A deep technical guide to how modern AI really works—from neural networks and transformers to RAG, embeddings, reasoning ...

Complex prediction problems often lead to ensembles because combining multiple models improves accuracy by reducing variance and capturing diverse patterns. However, these ensembles are impractical in ...

Attention-based architectures are a powerful force in modern AI. In particular, the emergence of in-context learning abilities enables task generalization far beyond the original next-token prediction ...

PyTorch code for SpERT: "Span-based Entity and Relation Transformer". For a description of the model and experiments, see our paper: https://arxiv.org/abs/1909.07755 ...

The recent breakthroughs of Large Language Models (LLMs) in the context of natural language processing have opened the way to significant advances in protein research. Indeed, the relationships ...

This repository contains slides for the course "20-00-0947: Deep Learning for Natural Language Processing" (Technical University of Darmstadt, Summer term 2023). This course is jointly lectured by ...

Introduction: Using MRI to synthesize CT and substitute its function in radiation therapy has drawn wide research interests. Currently, deep learning models have become the first choice for MRI—CT ...