We show that Gaussian RBMs can generate good images just like other generative models, despite the single-layer architecture. Key innovations:
1) Gibbs-Langevin sampling;
2) modified Contrastive Divergence.
Paper: https://t.co/pZk1TDzpfR
Code: https://t.co/u6ZNVOrZww
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Interested in how to generate realistic human trajectories using diffusion with just one step🤔?
This is now possible with MoFlow, a one-step Flow Matching method accompanied with Implicit Maximum Likelihood Estimation based distillation.
🚀 Join us at #CVPR2025 in Nashville!
Want to generate realistic hand–object manipulations for unseen objects?
Check out our new paper: "LatentHOI: On the Generalizable Hand Object Motion Generation with Latent Hand Diffusion".
Appearing at #CVPR2025 in Nashville!
🚀Our new work (RetroSynFlow) on retrosynthesis:
1) SOTA discrete flow matching that leverages synthons: products->synthons->reactants
2) effective test-time reward steering
Led by my amazing students @RobinY798, @qi_yan98, with stellar collaborators Guy Wolf & @bose_joey
Excited to announce RetroSynFlow, a discrete flow matching framework for diverse and accurate retrosynthesis!
📄Paper available here: https://t.co/Z4mgEfdjES
Joint work w/ @qi_yan98 , Guy Wolf, @bose_joey and @lrjconan .
👇 A quick overview 🧵
Led by my undergrad intern Nick Zhang (@VectorInst) and my PhD student Donglin Yang @ydlin718 at @ECEUBC.
Huge shoutout to them for driving this forward! 🙌
Code: https://t.co/dmiTi7Or2i
Paper: https://t.co/GgIs2HsKJS
Ever wondered how card shuffling can help solve combinatorial problems like sorting, jigsaw puzzles, or TSPs?
Our ICLR 2025 (Oral) paper SymmetricDiffusers introduces a novel discrete diffusion model on finite symmetric groups to solve them in a unified and principled way!
Interested in LLMs for math reasoning? Check out our new work that builds 647K Math QA pairs and A Live Math Benchmark that is kept up-to-date, led by my brilliant students @sadegh_mahdavi4@LiJonassen and Kaiwen!
🚀 Training an LLM for math reasoning, but high-quality data is scarce and costly?
Check out our paper: “Leveraging Online Olympiad-Level Math Problems for LLM Training & Contamination-Resistant Evaluation.” 📖✨
TL;DR:
🔹 LLM-powered pipeline for scalable, high-quality data collection 🤖
🔹 647K Math QA pairs 📊
🔹 A Live Math Benchmark that is kept up-to-date⏳
Paper: https://t.co/sTmiWn8aAj
Code & Data: https://t.co/qy3NKOlvlY
Project Website: https://t.co/ER84nE1x34
Evaluation Leaderboard: https://t.co/K73k65LAFM
@askalphaxiv (for QA): https://t.co/aE0RDdz4gF
It means a lot to someone who has worked on Hopfield networks and Boltzmann machines. John and Geoff's foundational work has inspired generations of scientists, and it will keep doing so! I now have a compelling reason to keep teaching and researching these models! Huge Congrats!
BREAKING NEWS
The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Physics to John J. Hopfield and Geoffrey E. Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural networks.”
⌛️We extended the submission deadline for the NeurIPS 2024 Workshop on Adaptive Foundation Models to October 4 AoE!
🏁Submission site: https://t.co/ZYcMeDyW1q
🌐Website: https://t.co/223K7rgD4W
Organizers: @mengyer, @PaulVicol, @NailaMurray, @lrjconan, @BeidiChen, @weichiuma