Etc

News

• Demystifying Diffusion-Based Models , NVIDIA (Dec 14, 2023)
• SD-XL Turbo , Open.AI (Nov 28, 2023)
• ZipLoRA , GitHub (Nov 22, 2023)
• Exploring Creation with Generative Models , D. Cohen-Or (Oct 03, 2023)
• Sneaky Prompt , arXiv (Nov 10, 2023)
• Fei-Lei Li new book , Wired (Nov 10, 2023)
• DevDay annoucements , OpenAI (Nov 06, 2023)
• Stablediffusion - Infinity , GitHub (Nov 05, 2023)
• Language, vision and generative models , Google (Jan 18, 2023)
• IA Sem Telas , O Globo (Nov 03, 2023)
• Nightshade: data poisoning tool , MIT TechReview (Oct 23, 2023)
• TED AI 2023 , (Oct 17-18, 2023)
• SteerLM: Customize LLMs During Inference , NVIDIA (Oct 11, 2023)
• Tiny Language Models Come of Age , Quanta (Oct 5, 2023)
• Reflections on ICCV over 31 years , Medium (Oct 15, 2021)
• ICCV 2023 Papers , github (Oct 3, 2023)
• Dream Gaussian , github.io (Sept 28, 2023)
• Emu , Meta Connect (Sept 27, 2023)
• New AI Experiences , Meta Connect (Sept 27, 2023)
• New Type of Generative AI , Quanta Magazine (Sept 22, 2023)
• ChatGPT can See, Hear & Speak , MIT Tech Review (Sept 25, 2023)
• On ChatGPT using your Voice , MIT Tech Review (Sept 25, 2023)
• ChatGPT agora tambem gera Imagens - veja o video (Sept 22, 2023)
• DALL-E 3 annouced (Sept 21, 2023)
• What's new in Photoshop , Adobe (Sept 15, 2023)
• Spellburst: LLM Interactive Canvas for Generative Artists (Sept 17, 2023)
• DeciDiffusion 1.0 (Sept 13, 2023)
• EfficientViT announced (Sept, 2023)
• Adobe releases Firefly Generative Model (Sept 14, 2023)
• SIGGRAPH 2023: Generative AI Theater -Playlist (Aug, 2023)
• The Godmother of Digital Image , NYT. (Sept 17, 2021)

Text to Image

• DALL-E 2
• Imagen
• Midjourney
• Crayon

• Disco Diffusion
• DALLE2-pytorch

Additional Material

• Introduction to Diffusion Models (2022)

• RANSAC in 2020 (CVPR 2020)
• RANSAC 30 years after (CVPR 2011)

Class Material

• A Decade in Computer Vision - Richard Szeliski

• Aula 03 - Machine Learning (2022)
• Aula 04 - Deep Learning (2022)

Related References

• Transformers as Support Vector Machines

• Every Model Learned by Gradient Descent Is Approximately a Kernel Machine

• Transformer (arquitetura implementada em python e pytorch)

• Inductive Biases and Variable Creation in Self-Attention Mechanisms

• Hidden Progress in Deep Learning