Join us at tomorrows #ICLR2024 oral session in the afternoon to learn about how we can turn neural networks into data! Afterwards Miltos Kofinas 🦋 @miltoskofinas.bsky.social Yan and I will be at the poster: #77 Graph Neural Networks for Learning Equivariant Representations of Neural Networks

ilya knows that it's time for weight-space architectures to shine :>

Come checkout our poster on CodeIt today at the #ICLR2024 #AGIWorkshop 4pm Halle A7. We tackle François Chollet’s ARC by self-improving LLMs with prioritized hindsight replay. Blaze(j) Manczak 🇵🇱🇱🇺🇪🇺 Auke Wiggers Corrado Rainone David Zhang Michaël Defferrard Taco Cohen

Dating a model Dating a model (2004) (2024)

Don't miss our survey on "Hyperbolic Deep Learning in Computer Vision: A Survey"!🙌 #IJCV

I'm hiring for a fully funded #PhD position in #ComputerVision on 'Detailed Video Understanding' at Leiden Computer Science Universiteit Leiden. Apply before 22nd June. More info👇 universiteitleiden.nl/en/vacancies/2…

ARC is a tough reasoning benchmark where modern LLMs far underperform humans still. Great to see that there's serious additional backing! Coincidentally, we just open-sourced CodeIt, our LLM-improvement approach for ARC: github.com/Qualcomm-AI-re…

Thanks, Kostas Daniilidis, Congyue Deng, and the team for inviting me. It's an honor to speak alongside this esteemed group of researchers! My talk will focus on our recent work on *Equivariant Weight Space Learning*: designing neural networks that can process other neural networks.

Our solution write-up for the 1st AIMO Progress Prize is now out ✍️! huggingface.co/blog/winning-a… In it, we share technical details on: ♾️💻 The 2-stage MuMathCode recipe we used to train NuminaMath 7B TIR with iterative SFT ⚖️ Evals on MATH - 56.3% for Stage 1 & 68.2% for Stage

Come see our poster #715 on CodeIt today at #ICML2024 13.30-15.00 Halle C. We approach ARC by self-improving LLMs with prioritized hindsight replay. Blaze(j) Manczak 🇵🇱🇱🇺🇪🇺 Auke Wiggers Corrado Rainone David Zhang Michaël Defferrard Taco Cohen

Pleasant surprise of ICML Conference: There is a growing Weight Space Learning Community out there - it was great to meet you all: Haggai Maron (Haggai Maron), Gal Chechik (Gal Chechik), Konstantin Schürholt (Konstantin Schürholt), Eliahu Horwitz (Eliahu Horwitz), Derek Lim (Derek Lim),

🚀 Exciting News! 🚀 I am more than happy to share that I have officially begun my research sabbatical this week! Over the coming months, I am fortunate to be working as TU/e Artificial Intelligence Systems Institute Visiting Professor at @TUeindhoven collaborating with Joaquin Vanschoren on some exciting ideas

Are you pursuing a PhD and are you interested in working on efficiency of LLMs/LVMs? Then join our model efficiency team in #QualcommAIResearch for an internship! Apply below, we have openings for 2025 as well as autumn/winter 2024. careers.qualcomm.com/careers/job/44…

🇪🇺 eu/acc A few weeks ago Mario Draghi asked my recommendations for his report that came out today about European competitiveness I had a call with him and summarized my problems with doing business in the EU I wrote this which is included in the report presented to the

Optimization can be sped up by 50% using our NiNo model! It takes a history of parameter values and predicts future parameters leveraging "neural graphs". Accelerating Training with Neuron Interaction and Nowcasting Networks: arxiv.org/abs/2409.04434 code: github.com/SamsungSAILMon…

🚨 Attention aspiring PhD students: Meta / FAIR is looking for candidates for a joint academic/industry PhD! 🚨 Among others, the CodeGen team is looking for candidates to work on world models for code, discrete search & continuous optimization methods for long-term planning,

📢Interested in #interning at #FAIR NY? Excited to share that I have one internship position available for #Summer2025 🙂! Looking for PhD interested in flow/diffusion models, optimal transport/control for structural problems. 🙌Send me your CV, website & GScholar by #Oct16th!

Want to do research in code generation with LLMs and wonky deep learning from the 90s? We're recruiting one Master student (M2) intern for 2025 at FAIR Paris in my team metacareers.com/jobs/106871446…

📢Thrilled to announce our ICLR 2025 ICLR 2026 workshop on Weight Space Learning, exploring model weights as a new data modality! 📢 Stay tuned for submission instructions and deadlines. openreview.net/pdf?id=Bz6wEdo… #weightspace #weightspacelearning #ICLR2025 #iclr

Our new workshop at ICLR 2025: Weight Space Learning: weight-space-learning.github.io Weights are data. We can learn from weights. Learning can outperform human-designed methods for optimization, interpretability, model merging, and more.