This week, we will present our recent #NeurIPS2024 paper.  📎 Paper: openreview.net/forum?id=HeoRs…  📆 Make sure to visit our poster #2600 on Fri, 13 December at 11 am!  Joint work with my amazing mentors Leon Hetzel Johanna Sommer Fabian Theis Stephan Günnemann

Excited to present our work on Neural Pfaffians at #NeurIPS. 🗣️ Oral: Friday 3:30pm, East Ballroom A, B 📊 Post: Friday 4:30pm - 7:30pm, East Exhibit Hall A-C #3600 📝 Paper: openreview.net/forum?id=HRkni… Happy to chat!

Excited to present our spotlight paper on uncertainty for GNNs at #NeurIPS! 📝Paper: openreview.net/pdf?id=6vNPPtW… 📆Come by our poster on Dec 12th at 11am! Thanks to my amazing collaborators Tom Wollschläger and Stephan Günnemann!

Make sure to stop by our #NeurIPS poster on Spatio-Spectral Graph Neural Networks (S²GNNs)! An efficient synergy of spatially & spectrally parametrised graph convolutions. Joint work w/ Simon Geisler Daniel Herbst Stephan Günnemann. 📎 openreview.net/pdf?id=Cb3kcwY… 📆 Dec 13, 11am, #4608

It’s rainy in Vancouver, poster hall is closed but we are ready 🙌 👉 Come and talk to us and learn about UniGuide at Poster#2600 (East) UniGuide is a new framework for molecular diffusion models that enables flexible geometric conditioning across tasks—no retraining required

Super happy & honored that our work on certifying NNs against poisoning won the Best Paper Award AdvMLFrontiers at #NeurIPS2024. Come by our poster 10:40am-12&4-5pm (or talk) tomorrow :) Joint work w/Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar & Stephan Günnemann L: arxiv.org/pdf/2407.10867

Generative Modeling with Bayesian Sample Inference Overview: Bayesian Sample Inference (BSI) formulates generative modeling as a Bayesian inference problem, where a sample is generated through a sequence of prediction and posterior update steps. BSI includes Bayesian Flow

Safe and reliable machine learning has never been more relevant. However, at the same time, LLMs made robustness research **more complex, less reproducible, and harder-to-evaluate**. How can we enable research progress despite these challenges?🧵 Stephan Günnemann Gauthier Gidel

Do you think your LLM is robust?⚠️With current adversarial attacks it is hard to find out since they optimize the wrong thing! We fix this with our adaptive, semantic, and distributional objective. By Stephan Günnemann's lab & Google AI, w/ Center for AI Safety support Here's how we did it. 🧵

I am truly excited to share our latest work with Michael Scherbela, Philipp Grohs, and Stephan Günnemann on "Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems"! arxiv.org/abs/2504.06087

Happy to share that our paper "Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space" got accepted to #ICLR2025, and we will be presenting it this week in Singapore! Joint work with Nicholas Gao, Tom Wollschläger, Johanna Sommer, and Stephan Günnemann. 🧵 1/

Excited to announce our #ICLR2025 spotlight work deriving the first exact certificates for neural networks against label poisoning 🎉. Joint work w/ Mahalakshmi Sabanayagam, Stephan Günnemann & Debarghya. For more details check out the thread below👇 or check out our paper arxiv.org/abs/2412.00537.

Thrilled to announce that we just presented „MAGNet: Motif-Agnostic Generation of Molecules from Scaffolds“ at #ICLR2025 🧲 Johanna Sommer Bastian Grossenbacher-Rieck Fabian Theis Stephan Günnemann For those who couldn’t make it to our spotlight: openreview.net/forum?id=5FXKg…

If you are attending #ICLR2025 and are interested in electronic structure modelling / quantum chemistry come by our poster on learnable non-local XC-functionals to discuss with Nicholas Gao and me. 🗓️ Today | 3:00 pm– 5:30 pm 📍Hall 3 | Poster #3

How do LLMs navigate refusal? Our new @ICMLConf paper introduces a gradient-based approach & Representational Independence to map this complex internal geometry. 🚨 New Research Thread! 🚨 The Geometry of Refusal in Large Language Models By Stephan Günnemann's lab & Google AI. 🧵👇