"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

#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 nice tutorial that explores the basics of the JAX ecosystem from the lens of a PyTorch user. #machinelearning #pytorch #jax

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.

cloud.google.com

"... 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.

simonsfoundation.org

"... 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

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.

simonsfoundation.org

"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...

✨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

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

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...

arxiv.org

"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

A mapping of how Bluesky is becoming the new Scientific Twitter mikeyoungacademy.dk/bluesky-is-e...

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.

mikeyoungacademy.dk

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... !

Gabriele Corso@gcorso.bsky.social · 2y ago

Thrilled to announce Boltz-1, the first open-source and commercially available model to achieve AlphaFold3-level accuracy on biomolecular structure prediction! An exciting collaboration with Jeremy, Saro, and an amazing team at MIT and Genesis Therapeutics. A thread!

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