"Graph Low-Rank Adapters of High Regularity for Graph Neural Networks and Graph Transformers" by PantelisPapageorgiou, Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, @mmbronstein.bsky.social

Paper: openreview.net/forum?id=gxh...
Code: github.com/PanPapag/GCo...

#graphneuralnetworks

"Towards Quantifying Long-Range Interactions in Graph Maine Learning: a Large Graph Dataset and a Measurement" by Huidong Liang, Haitz Sáez de Ocáriz Borde, Baskaran Sripathmanathan, @mmbronstein.bsky.social, Xiaowen Dong

Paper: arxiv.org/abs/2503.09008

#graphneuralnetworks #machinelearning

Of course: diffusion.csail.mit.edu

#diffusionmodels

There is a more clean and fresh air with the blue sky! 😉

"The Jungle of Generative Drug Discovery: Traps, Treasures, and Ways Out" by Rıza Özçelik, @fragrisoni.bsky.social

Paper: arxiv.org/abs/2501.05457

#machinelearning

"Tutorial on Diffusion Models for Imaging and Vision" by Stanley Chan

Paper: arxiv.org/abs/2403.18103

#machinelearning #diffusionmodels

"Task Singular Vectors: Reducing Task Interference in Model Merging" by Antonio Andrea Gargiulo, @crisostomi.bsky.social , @mariasofiab.bsky.social , @sscardapane.bsky.social, Fabrizio Silvestri, Emanuele Rodolà

Paper: arxiv.org/abs/2412.00081
Code: github.com/AntoAndGar/t...

#machinelearning

A guide to JAX for PyTorch developers | Google Cloud Blog PyTorch users can learn about JAX in this tutorial that connects JAX concepts to the PyTorch building blocks that they’re already familiar with.

A nice tutorial that explores the basics of the JAX ecosystem from the lens of a PyTorch user.

#machinelearning #pytorch #jax

Watch: Jim Simons’ Life, Legacy and 5 Guiding Principles A short film chronicles Simons Foundation co-founder Jim Simons’ careers as a mathematician, the founder of Renaissance Technologies and a philanthropist.

"... The secret sauce is hiring great people, providing a great infrastructure, collaborating across the board, and sharing profits with everyone. ..." - Jim Simons

#leadership #math #science #finance

Watch: Jim Simons’ Life, Legacy and 5 Guiding Principles A short film chronicles Simons Foundation co-founder Jim Simons’ careers as a mathematician, the founder of Renaissance Technologies and a philanthropist.

"... The secret sauce is hiring great people, providing a great infrastructure, collaborating across the board, and sharing profits with everyone. ..." - Jim Simons

#leadership hashtag#math hashtag#science hashtag#finance

"EM Distillation for One-step Diffusion Models" by Sirui Xie, Zhisheng Xiao, @dpkingma.bsky.social, Tingbo Hou, Ying Nian Wu, Kevin Murphy, Tim Salimans, Ben Poole, @ruiqigao.bsky.social

Paper: arxiv.org/abs/2405.16852

#machinelearning #diffusionmodels

*A Journey into PyTorch, the Ecosystem, and Deep Learning Compilers*

Great seminar by @lantiga.bsky.social on the compiler's ecosystem and the recent Thunder framework by LightningAI! I have uploaded slides, video, & notebooks publicly. 🙂

www.sscardapane.it/seminars/pyt...

“Gratitude is a noble virtue. Live with gratitude and your heart will expand.” - Stephen R. Covey

Happy Thanksgiving to everyone who celebrates!

#happythanksgiving

Congrats @ian-goodfellow.bsky.social, @yoshuabengio.bsky.social and coauthors on your test of time @neuripsconf.bsky.social award about GAN seminal paper! Very well deserved!

blog.neurips.cc/2024/11/27/a...

Screen capture of LoG website. The conference is Nov 26-29, 2024. See our website for more details: https://logconference.org/.

✨EXCITING NEWS! We now have a Bluesky account!!

AND registration for the 3rd Learning on Graphs conference is open 😊

It is virtual, free to attend, livestreamed, and recorded 📹 Sign up today! The conference is this coming week 😱

forms.gle/eYiDCopJGUc8...

Graph Neural Networks Do Not Always Oversmooth" by Bastian Epping, Alexandre René, Moritz Helias, and Michael Schaub

Paper: arxiv.org/abs/2406.02269

#graphneuralnetworks

Gradient scarcity with Bilevel Optimization for Graph Learning A common issue in graph learning under the semi-supervised setting is referred to as gradient scarcity. That is, learning graphs by minimizing a loss on a subset of nodes causes edges between unlabel...

Our #TMLR paper "Gradient scarcity with Bilevel Optimization for Graph Learning" (w/ H Ghanem, @samuelvaiter.com) was accepted as an oral presentation at the Learning on Graphs conference 🤓
100% free and online, come check it out!
logconference.org

arxiv.org/abs/2303.13964

"Trajectory Flow Matching with Applications to Clinical Time Series Modeling" by Xi Zhang, Yuan Pu, Yuki Kawamura, Andrew Loza, @yoshuabengio.bsky.social, Dennis Shung, Alexander Tong

Paper: arxiv.org/abs/2410.21154
#machinelearning

"gRNAde: Geometric Deep Learning for 3D RNA inverse design" by @chaitjo.bsky.social , @arian-jamasb.bsky.social, Ramon Viñas, Charles Harris, Simon Mathis, Alex Morehead, Rishabh Anand, and Pietro Liò

Paper: www.biorxiv.org/content/10.1...

Code: github.com/chaitjo/geom...

#geometricdeeplearning

"Enhancing the Expressivity of Temporal Graph Networks through Source-Target Identification" Benedict Aaron Tjandra, Federico Barbero, @mmbronstein.bsky.social

#graphneuralnetworks

Bluesky is emerging as the new platform for science - Mike Young Academy Scientific Twitter is about to find its true successor. And it is not X. This, our latest release, shows that the Bluesky network of scientists is growing — and growing.

A mapping of how Bluesky is becoming the new Scientific Twitter

mikeyoungacademy.dk/bluesky-is-e...

This place is growing fast and with a lot of nice people!

#bluesky

The preprint is now on bioRxiv www.biorxiv.org/content/10.1... and the model on HuggingFace 🤗 huggingface.co/boltz-commun... !

I fell on the keyboard and bought a bunch of physics textbooks (and one intruder). 😅 With great suggestions from @sgiagu.bsky.social @wellingmax.bsky.social

"Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges" by @mmbronstein.bsky.social, Joan Bruna, Taco Cohen, @petar-v.bsky.social

#geometricdeeplearning