Started a list of some researchers working on image/video generation. (Not comprehensive at all)
Reply with a paper link and TLDR to get added to the list! I request all grad students to not feel imposter-y and just reply if you work in this field!
#computervision#diffusiongo.bsky.app/SP1uWoE
About to send my last DLCT email of the year today (in 2 hours).
Join the 7-year-old mailing list if you haven't heard of it. (And if you have heard of it but haven't joined, I trust that it's a well thought decision that suits you the best.)
groups.google.com/g/deep-learn...
The recording of my #NeurIPS2024 workshop talk on multimodal iterative refinement is now available to everyone who registered: neurips.cc/virtual/2024...
My talk starts at 1:10:45 into the recording.
I believe this will be made publicly available eventually, but I'm not sure when exactly!
congratulations, @ian-goodfellow.bsky.social, for the test-of-time award at @neuripsconf.bsky.social!
this award reminds me of how GAN started with this one email ian sent to the Mila (then Lisa) lab mailing list in May 2014. super insightful and amazing execution!
Trying to build a "books you must read" list for my lab that everyone gets when they enter. Right now its:
- Sutton and Barto
- The Structure of Scientific Revolutions
- Strunk and White
- Maybe "Prediction, Learning, and Games", TBD
Kinda curious what's missing in an RL / science curriculum
This is a simple and good paper, which somehow nobody working on these things cites, or even seems to be aware of arxiv.org/abs/2406.05213 It is simple idea that seems useful; it formulates the subjective uncertainty for natural language generation in a decision-theoretic setup.
let me say it once more: "the gap between OAI/Anthropic/Meta/etc. and a large group of companies all over the world you've never cared to know of, in terms of LM pre-training? tiny"
Interesting paper on arxiv this morning: arxiv.org/abs/2411.13683
It's a video masked autoencoder in which you learn which tokens to mask to process fewer of them and scale to longer videos. It's a #NeurIPS2024 apparently.
I wonder if there could be such strategy in the pure generative setup.
Discrete diffusion has become a very hot topic again this year. Dozens of interesting ICLR submissions and some exciting attempts at scaling. Here's a bibliography on the topic from the Kuleshov group (my open office neighbors).
github.com/kuleshov-gro...
In a gratuitous attempt to acquire more followers myself 😁, I've made a start on a "starter pack". Hopefully as more people from 🐦 make it over to 🦋, we can extend this a bit. Suggestions welcome!
I've noticed not all accounts seem to be eligible to be added, anyone know what's up with that? 🤔
Importantly, starter packs are intended as a way for newcomers to the platform to conveniently get started with finding people from their community. They cannot and should not be considered authoritative “VIP lists.”
I'm slowly putting my intro to ML course material on github, starting with the lab sessions: github.com/davidpicard/...
These are self-contained notebooks in which you have to implement famous algorithms from the literature (k-NN, SVM, DT, etc), with a custom dataset that I (painstakingly) made!
What are some must-read multimodal generation papers? I am looking for vision-language models (preferably jointly trained from scratch).
Some examples -
Chameleon - arxiv.org/abs/2405.09818
Transfusion - arxiv.org/abs/2408.11039
JanusFlow - arxiv.org/abs/2411.07975#computervision#multimodal
6 years ago, in the days of GAN art, I wrote an article called "Can Computers Create Art?", arguing that computers should not be considered artists, regardless of how good image generation gets. People sometimes ask if my views have changed. I say, 1/🧵
www.mdpi.com/2076-0752/7/...
Here's my attempt at assembling a starter pack of the still nascent computer vision community on Bluesky. Feel free to recommend other accounts that should be in this starter pack. :) #computervision (Do we use hashtags here? 😅)
go.bsky.app/PkAKJu5