Two great works on how we can manipulate style for generative modeling by PiMa!

🤔 What happens when you poke a scene — and your model has to predict how the world moves in response?

We built the Flow Poke Transformer (FPT) to model multi-modal scene dynamics from sparse interactions.

It learns to predict the 𝘥𝘪𝘴𝘵𝘳𝘪𝘣𝘶𝘵𝘪𝘰𝘯 of motion itself 🧵👇

🤔When combining Vision-language models (VLMs) with Large language models (LLMs), do VLMs benefit from additional genuine semantics or artificial augmentations of the text for downstream tasks?

🤨Interested? Check out our latest work at #AAAI25:

💻Code and 📝Paper at: github.com/CompVis/DisCLIP

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🤔 Why do we extract diffusion features from noisy images? Isn’t that destroying information?

Yes, it is - but we found a way to do better. 🚀

Here’s how we unlock better features, no noise, no hassle.

📝 Project Page: compvis.github.io/cleandift
💻 Code: github.com/CompVis/clea...

🧵👇

me right now..

Hi, just sharing an updated version of the PyTorch 2 Internals slides: drive.google.com/file/d/18YZV.... Content: basics, jit, dynamo, Inductor, export path and executorch. This is focused on internals so you will need a bit of C/C++. I show how you can export and run a model on a Pixel Watch too.

While we're starting up over here, I suppose it's okay to reshare some old content, right?

Here's my lecture from the EEML 2024 summer school in Novi Sad🇷🇸, where I tried to give an intuitive introduction to diffusion models: youtu.be/9BHQvQlsVdE

Check out other lectures on their channel as well!