Joan Serrà
@serrjoa.bsky.social
310 followers 150 following 23 posts
Does research on machine learning at Sony AI, Barcelona. Works on audio analysis, synthesis, and retrieval. Likes tennis, music, and wine. https://serrjoa.github.io/
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serrjoa.bsky.social
I think I may switch back to Twitter/X. Somehow I feel this site didn't take off and I really don't want to be looking at two feeds all the time...
serrjoa.bsky.social
I don't know. I could just now...
serrjoa.bsky.social
I think I may switch back to Twitter/X. Somehow I feel this site didn't take off and I really don't want to be looking at two feeds all the time...
Reposted by Joan Serrà
ducha-aiki.bsky.social
Image matching and ChatGPT - new post in the wide baseline stereo blog.

tl;dr: it is good, even feels like human, but not perfect.
ducha-aiki.github.io/wide-baselin...
ChatGPT and Image Matching – Wide baseline stereo meets deep learning
Are we done yet?
ducha-aiki.github.io
Reposted by Joan Serrà
andrewgwils.bsky.social
Many of the greatest papers, now canonical works, have a story of resistance, tension, and, finally, a crucial advocate. It's shockingly common. Why is there a bias against excellence? And what happens to those papers, those people, when no one has the courage to advocate?
serrjoa.bsky.social
Preferred qualifications:
- PhD candidate or Postdoc.
- Experience with representation/contrastive learning or generative music models.
- Strong programming skills.
- Strong mathematical background.
- Python, github, pytorch, ...
- EU residence permit.
👇
serrjoa.bsky.social
Topics: representation learning for music matching or generative models for music copyright.
Location: Barcelona, on-site (two days a week at least).
Duration: 4-6 months.
Start date: April-November 2025.
Dedication: full-time (part-time also an option).
👇
serrjoa.bsky.social
Do you want to work with me for some months? Two internship positions available at the Music Team of Sony AI in Barcelona!
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Views from the office window. Photo taken just now.
serrjoa.bsky.social
Haha, me maybe not, but someone should go...
serrjoa.bsky.social
Congrats to my colleagues, many of whom are not on this website!
serrjoa.bsky.social
I'm happy to have two papers accepted at #ICASSP2025!

1) Contrastive learning for audio-video sequences, exploiting the fact that they are *sequences*: arxiv.org/abs/2407.05782

2) Knowledge distillation at *pre-training* time to help generative speech enhancement: arxiv.org/abs/2409.09357
serrjoa.bsky.social
Flow matching mapping text to image directly (instead of noise to image): cross-flow.github.io
Reposted by Joan Serrà
kolesnikov.ch
With some delay, JetFormer's *prequel* paper is finally out on arXiv: a radically simple ViT-based normalizing flow (NF) model that achieves SOTA results in its class.

Jet is one of the key components of JetFormer, deserving a standalone report. Let's unpack: 🧵⬇️
Reposted by Joan Serrà
dlbcnai.bsky.social
Did you miss any of the talks of the Deep Learning Barcelona Symposyum 2024 ? Play them now from the recorded stream:

www.youtube.com/live/yPc-Un3...
YouTube
Share your videos with friends, family, and the world
www.youtube.com
Reposted by Joan Serrà
howard.fm
I'll get straight to the point.

We trained 2 new models. Like BERT, but modern. ModernBERT.

Not some hypey GenAI thing, but a proper workhorse model, for retrieval, classification, etc. Real practical stuff.

It's much faster, more accurate, longer context, and more useful. 🧵
serrjoa.bsky.social
On pre-acrivation norm, learnable residuals, etc.
giffmana.ai
A post by @cloneofsimo on Twitter made me write up some lore about residuals, ResNets, and Transformers. And I couldn't resist sliding in the usual cautionary tale about small/mid-scale != large-scale.

Blogpost: lb.eyer.be/s/residuals....
Reposted by Joan Serrà
kastnerkyle.bsky.social
Two great tokenizer blog posts that helped me over the years: sjmielke.com/papers/token...

sjmielke.com/comparing-pe...

People have mostly standardized on certain tokenizations right now, but there are huge performance gaps between locales with high agglomeration (e.g. common en-us) and ...
serrjoa.bsky.social
Don't be like Reviewer 2.
Reposted by Joan Serrà
docmilanfar.bsky.social
Did Gauss invent the Gaussian?

- Laplace wrote down the integral first in 1783
- Gauss then described it in 1809 in the context of least-sq. for astronomical measurements
- Pearson & Fisher framed it as ‘normal’ density only in 1910

* Best part is: Gauss gave Laplace credit!
serrjoa.bsky.social
I already signed up (as a mentor) for this year!
dlbcnai.bsky.social
Call for mentees and mentors open until December 16.

Sign up as a mentee if you are a student or in the early stages of your career.

Sign up as a mentor to help in the career growth of a member of the #DLBCN community.

Details and registration:
sites.google.com/view/dlbcn20...
Reposted by Joan Serrà
jfranke.bsky.social
Thrilled to present our work on Constrained Parameter Regularization (CPR) at #NeurIPS2024!
Our novel deep learning regularization outperforms weight decay across various tasks. neurips.cc/virtual/2024...
This is joint work with Michael Hefenbrock, Gregor Köhler, and Frank Hutter
🧵👇
NeurIPS Poster Improving Deep Learning Optimization through Constrained Parameter RegularizationNeurIPS 2024
neurips.cc
Reposted by Joan Serrà
keenancrane.bsky.social
Entropy is one of those formulas that many of us learn, swallow whole, and even use regularly without really understanding.

(E.g., where does that “log” come from? Are there other possible formulas?)

Yet there's an intuitive & almost inevitable way to arrive at this expression.
Reposted by Joan Serrà
iscienceluvr.bsky.social
Inventors of flow matching have released a comprehensive guide going over the math & code of flow matching!

Also covers variants like non-Euclidean & discrete flow matching.

A PyTorch library is also released with this guide!

This looks like a very good read! 🔥

arxiv: arxiv.org/abs/2412.06264