Critical Windows: Non-Asymptotic Theory for Feature Emergence in Diffusion Models
Explore non-asymptotic theory for feature emergence in diffusion models, focusing on critical windows and their implications for generative AI and machine learning.
Toward Building a Cost-Effective and Robust Machine Learning System
Explore cost-effective ML system development through active learning, continual learning, and transfer learning. Learn efficient model selection techniques for optimal source model transfer to target tasks.
Generative AI and Large Language Models: Recent Advancements and Challenges
Explore generative AI advancements, challenges, and VinAI's contributions with Dr. Hung Bui. Gain insights into AI-generated content's impact and the pressing issues in this rapidly evolving field.
Image Gradients for Understanding and Improving Neural Networks
Explore image gradients in neural networks to synthesize adversarial examples, visualize neurons, enhance robustness, interpret decisions, and improve image generators.
Neural Scene Representations for Learning-based View Synthesis and Its Applications
Explore neural scene representations for efficient image generation, novel view synthesis, and advanced applications in computer graphics and 3D vision.
NeuPSL - Experiments and Results - Part 3
Explore experimental results of NeuPSL, a neurosymbolic framework combining probabilistic soft logic with deep learning for end-to-end training and logical constraint enforcement.
Introduction to Language Models - LLMs, Prompt Engineering, and Architectures
Explore language models, covering generative AI, LLMs, encoders, prompt engineering, and transformer architecture. Gain insights into embeddings, attention mechanisms, and model limitations.
Certifying Trustworthy Deep Learning Systems
Explore techniques for certifying trustworthiness in deep learning systems with expert insights from Linyi Li, enhancing AI reliability and safety.
Modelling and Controlling Turbulent Flows through Deep Learning
Explore deep learning applications in modeling and controlling turbulent flows, from flow reconstruction to reinforcement learning for flow control, with insights on CNN architectures and transfer learning.
The Geometry of the Deep Linear Network
Explore the geometric principles underlying deep linear networks, uncovering their mathematical foundations and implications for machine learning algorithms.
Unlocking LLM Performance with eBPF - Optimizing Training and Inference Pipelines
通过eBPF实现LLM训练和推理过程的可观察性,优化性能。介绍内存、网络和GPU分析方法,分享在PyTorch和llm.c项目中的实践经验,提高GPU利用率。
Functional Programming and Scala for Machine Learning - YOW! 2015
Explore how functional programming and Scala can revolutionize machine learning, offering strongly-typed solutions for efficient algorithm implementation and scalable data processing.
Training LoRA with SimpleTuner and AI-Toolkit for FLUX.1 - Art Style and Concept Development
Comprehensive guide on training LoRA models for FLUX.1 [dev], covering techniques, experiments, and analysis for art style and concept generation in Stable Diffusion.
Building a Deep Learning Model for Ship Detection Using YOLOv8
Implement YOLOv8 for ship detection in sea views using Python. Learn data preparation, model training, and prediction visualization for effective object detection.
Creating a Horse Race Detection Model using Deep Learning
Learn to create a horse race detection model using deep learning without a pre-existing dataset. Extract frames, automate annotations, train YOLOv8, and apply the model to videos for real-time object detection.
Deep Learning for Basketball Game Detection - YOLOv8 Object Detection Tutorial
Develop a custom YOLOv8 model for real-time basketball object detection, covering automatic labeling, model training, and live inference on game footage.
Dog Breed Detection using YOLOv8 and Deep Learning
Learn to build a YOLOv8-based dog breed detection system using deep learning. Master data preparation, model training, and making predictions with bounding boxes.
Create GUI App with Stable Diffusion, Docker, and Flask - Beginner Friendly
Learn to build a text-to-image AI app using Stable Diffusion, Docker, and Flask. Create high-res images from text prompts, explore Docker Init, CUDA, FreeU, and more in this beginner-friendly Python tutorial.
Metric Space Magnitude and Generalization in Neural Networks
Exploring metric space magnitude in neural networks: new topological complexity measures for assessing generalization capabilities, with applications to transformers and deep graph networks.
Attention to Quantum Complexity
Explore quantum complexity through advanced concepts and cutting-edge research, presented by Cornell University expert Eun-Ah Kim at a prestigious international conference.
LLaMA 3 Deep Dive - Synthetic Data, Privacy, and Model Architecture
Explore LLaMA 3's innovations with Meta's Thomas Scialom, covering synthetic data, privacy concerns, scaling techniques, and architectural choices in this in-depth discussion on advanced language models.