Aitor González-Marfil

PhD student | Deep Learning | Computer Vision | Biomedical Images

[Kevin Zhang @kevinzhang25]

while doing ML research i spend a disproportionately large amount of time looking at this specific figure

[BiaPy @BiaPyX]

🧬 BiaPy was built by an international collaboration between researchers from @upvehu, @DIPCehu, @BiofisikaScienc, @UC3M, @scu_lab, @LabOptBio and others — led by @IgnacioArganda and @ArrateMunoz.
A huge thanks to everyone who contributed! 🌟 (5/7)

[Aitor González-Marfil @AAitorG]

But there are no restrictions on its use! Feel free to experiment with other types of data and see what works for you. 🚀

[Aitor González-Marfil @AAitorG]

My first preprint is out!
"DINOSim: Zero-Shot Object Detection and Semantic Segmentation on Electron Microscopy Images" 🔬✨

🔗: https://t.co/wQK84pvHrg

[Aitor González-Marfil @AAitorG]

DINOSim was created to provide a functional tool for environments with limited resources, little data, no labels, or no access to large model training, a common challenge in many biomedical labs.

[Aitor González-Marfil @AAitorG]

A few months ago, I had the opportunity to present my project, DINOSim, at #SPAOM2024. It was an incredible experience where I had the opportunity to meet and share ideas with many amazing people.

[Ignacio Arganda-Carreras @IgnacioArganda]

🧪🔬 Are you at #SPAOM2024 ? Here you have a list of the contributions from my lab (all in Day 2 and 3)👇

1⃣ Tomorrow at 10:15am (Sala Toledo) my PhD student @AAitorG will present his work "Zero-Shot Object Detection with Foundational Models: A Similarity-Based Approach"

[Estibaliz Gómez de Mariscal, PhD @gomez_mariscal]

#SPAOM2024 attendants don't miss @AAitorG's talk on #ZeroShot #segmentation 👇 and catching him up later!

[BiaPy @BiaPyX]

🆕 We have updated our preprint in @biorxivpreprint 📰 It explains better the current state of #BiaPy ⛴️ while describing as well its limitations 🤗 Hope you like it!
"BiaPy: Accessible deep learning on bioimages" https://t.co/nAJ5159xVs

[Tanishq Mathew Abraham, Ph.D. @iScienceLuvr]

I remember during my PhD,

I spent many many hours reviewing every single image in my datasets, while I just used an off-the-shelf GAN architecture for my models because I observed that

dataset quality >>>> model arch

[Yann LeCun @ylecun]

DINOv2, the cutting-edge computer vision model trained through self-supervised learning to produce universal features, is now available under the Apache 2.0 license.

Onward with open source AI.

[Yann LeCun @ylecun]

I-JEPA: Efficient method for Self-Supervised Learning of image features.
No need for data augmentation, just masking.
Joint embedding predictive architecture, not generative.
And it's open source, of course.

Blog: https://t.co/ZuouZgeEMC
Paper: https://t.co/BoHSnELyw8
Code & models: https://t.co/DgS9XiwnMz

[Dimitris Papailiopoulos @DimitrisPapail]

GPT-4 "discovered" the same sorting algorithm as AlphaDev by removing "mov S P".

No RL needed. Can I publish this on nature?

here are the prompts I used https://t.co/FWAsE81lyq
(excuse my idiotic typos, but gpt4 doesn't mind anyways)

[Tom Goldstein @tomgoldsteincs]

#OpenAI is planning to stop #ChatGPT users from making social media bots and cheating on homework by "watermarking" outputs. How well could this really work? Here's just 23 words from a 1.3B parameter watermarked LLM. We detected it with 99.999999999994% confidence. Here's how 🧵

[Xander Steenbrugge @xsteenbrugge]

This is a "3D-diffusion" video created using a combination of four different AI models🤯

Welcome to the metaverse! 🌌😎

There's such incredible potential here that I want to explain how I made this, so here's a thread! (1/n)

[AK @_akhaliq]

CLIPasso: Semantically-Aware Object Sketching
abs: https://t.co/di8qNOfC7j
project page: https://t.co/b5WCuRfWxc