LLMOps: Fine-Tuning Video Classifier (ViViT) with Custom Data
Fine-tune a Video Vision Transformer (ViViT) using custom datasets. Learn to adapt Google's pretrained model for specialized video classification tasks.
Local Flux.1 LoRA Training Using AI-Toolkit
Learn to create custom LoRAs for Flux.1 image generation on your PC, enhancing style and object control. Explore the process, requirements, and potential future developments in AI image customization.
Flux.1 Image-to-Image and LLM Prompt Enhancement in ComfyUI
Explore image-to-image composition control and AI-assisted prompt enhancement in ComfyUI, featuring Flux.1 workflows and LLM integration for improved image generation.
ControlNet Union ProMax, Pixart Sigma 900M, and New ComfyUI Features
Explore new ComfyUI features: ControlNet Union ProMax, Pixart Sigma 900M, improved background removal, and more. Enhance your AI image generation capabilities with these free tools.
Microsoft AI: ML.NET Framework in C# - Transfer Learning for Image Classification
Aprende a entrenar modelos de aprendizaje profundo personalizados utilizando transferencia de aprendizaje, TensorFlow y ML.NET para clasificar imágenes de superficies de concreto.
Fine-Tuning ViT Classifier with Retina Images and Converting to ONNX - Video 3
Fine-tune a Vision Transformer for diabetic retinopathy detection using EyeQ dataset and convert the model to ONNX format for efficient deployment.
Phenomics in Drug Discovery: Microscopy and Machine Learning - Day 4
Explore phenomics in drug discovery through microscopy and machine learning techniques with expert Anne Carpenter.
Less is More: Learning Signals to Learn Representations in Healthcare
Explore advancements in machine learning for MRI reconstruction and medical imaging. Discover how less data can yield more accurate representations in healthcare applications.
Out of Distribution Generalization
Explore out-of-distribution generalization techniques, focusing on nuisance-induced spurious correlations and invariant risk minimization. Gain insights into robust neural networks and counterfactual invariance.
A Computational Study of the Internal Structure of Historical Papers - Leonardo da Vinci's Notebooks
Explore computational techniques to analyze Leonardo da Vinci's manuscripts, revealing hidden structural features and enhancing understanding of their origin, sequence, and chronology.
Understanding ChatGPT and Neural Networks for Human-Like Tasks
Explore the inner workings of ChatGPT and large language models, delving into neural networks, model fitting, and machine learning techniques for human-like tasks.
Computational Analysis of Liver Whole Slide Images Empowers Genomic Analyses of Historical Traits
Explore computational analysis of liver whole slide images to enhance genomic studies of historical traits. Learn advanced techniques for quantifying histologic features in non-alcoholic steatohepatitis.
Train a Production-Level Image Classifier
Learn to build a robust image classifier using advanced techniques like data augmentation, transfer learning, and learning rate scheduling.
Approximately Piecewise E(3) Equivariant Point Networks
Explore APEN: a framework for approximate piecewise-E(3) equivariant point networks, improving generalization in part-based symmetry tasks like room scene analysis and human motion recognition.
New Additions to Wolfram Neural Net Repository - Overview and Applications
Explore the latest pre-trained models in Wolfram's Neural Net Repository, covering NLP, computer vision, and audio analysis, with insights on their applications and integration.
What's New in Wolfram Image and Audio Processing - Recent Developments and Applications
Explore cutting-edge AI advancements in image and signal processing, including segmentation, OCR, and speech technologies, with powerful neural network applications.
Get Started with AI - A Beginner's Guide to Automated Classification, Predictions and Computer Vision
Apply modern data science techniques for predictions, categorization, and relationship discovery using numeric, textual, and image data. Learn practical AI applications for beginners.
XAI: A Model to Explain StyleGANs
Explore an innovative explanation model for StyleGANs using active shape and appearance models in this computational essay.
D-Flow: Differentiating through Flows for Controlled Generation
Explore D-Flow framework for controlled generation in AI models, optimizing source points through flow differentiation. Learn applications in inverse problems and conditional generation.
Uncovering and Inducing Interpretable Causal Structure in Deep Learning Models
Explore causal abstraction theory for uncovering and inducing interpretable structures in deep learning models, focusing on faithful explanations and interventions during analysis and training.
MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation
Explore MultiDiffusion: a framework for controllable image generation using pre-trained diffusion models. Learn about panorama creation, high-resolution outputs, and versatile user controls without retraining.