xLSTM for Real-Time DNS Tunnel Detection: arxiv.org/abs/2512.09565 DNS-HyXNet = xLSTM for DNS tunnels. DNS-HyXNet has 99.99% accuracy, with F1-scores exceeding 99.96%, and per-sample detection latency of just 0.041 ms, confirming its scalability and real-time readiness. wow!

Sepp Hochreiter, Head of LIT AI Lab, comments on the EurIPS conference in this FAZ guest article: He highlights Europe’s growing visibility in AI research and the role of ELLIS in strengthening the community. 🌍 www.faz.net/pro/digitalw...

The Great Comeback of Self-Normalizing Networks in 2025: It’s been a wild year in AI and for SNNs + SELU!! See my overview and some trends here: bioinf-jku.github.io/SNNs/

Great news for AI research at JKU! Upper Austria invests €22.5M to strengthen AI & quantum science, supporting the ELLIS Unit Linz and the LIT AI Lab. This commitment boosts new projects, talent, collaborations & innovation made in Austria 🇦🇹 www.nachrichten.at/politik/land...

Thanks for more than 1000 visits to the leaderboard in the last 2 days! YOU THINK YOU HAVE A BETTER MODEL?? GREAT! Training models on the Tox21 Challenge dataset can be done on a laptop-GPU. Submit your model to the leaderboard! Click SUBMIT here: huggingface.co/spaces/ml-jk...

AI is hitting a wall in drug discovery! Here is the wall you were all looking for... huggingface.co/spaces/ml-jk...

Measuring AI Progress in Drug Discovery - A NEW LEADERBOARD IN TOWN 2015-2025: turns out that there's hardly any improvement. AI bubble? GPT is at 70% for this task, whereas the best methods get close to 85%. Leaderboard: huggingface.co/spaces/ml-jk... P: arxiv.org/abs/2511.14744

List of accepted contributions now online: moleculediscovery.github.io/workshop2025/

Roughly 50% of the tickets already gone...

Hab mir einen Mahrer Tracker gebaut. Spannend zu sehen, wie schnell Print-Medien auf ihren Online-Portalen auf Dinge wie ein ZIB 2 Interview reagieren und wie sich die Inhalte dabei unterscheiden.

ELLIS ML4Molecules Workshop 2025: Registration for virtual participation now open!!! Only 500 tickets available which usually are gone fast!! Register now: www.eventbrite.com/e/ellis-mach...

Speaker 4 at ELLIS ML4Molecules 2025: Nadine Schneider Early works on ML methods for chemical reactions. Introduced the FS-Mol datasets for few-shot learning for molecules. Director of the ELLIS ML for Molecules Discovery program. Join the workshop: moleculediscovery.github.io/workshop2025/

Invited speaker 3 at #ML4Molecules2025: Daniel Probst ( @skepteis.bsky.social ). He is known for his works on exploring chemical spaces, fingerprints, language models,... and some unconventional ideas like learning on gzip compressed data. Join: moleculediscovery.github.io/workshop2025/

@marwinsegler.bsky.social will talk about "Deep Learning for Molecules: The First Decade" at #ML4Molecules2025 In pioneering work, he introduced a "small LLM" for generating SMILES strings back in 2016/17. Chemical synthesis prediction with MCTS; ... Join: moleculediscovery.github.io/workshop2025/

(I/III) We're excited to announce a new tenure track opening! The position is called 'quantum informatics' and is affiliated with our QUICK group within the CS+AI division at @jku.at 🇦🇹. Application deadline is November 30th, 2025: www.jku.at/en/the-jku/w...

Celebrating 4,000 citations! Thanks to everyone who successfully used self-normalizing networks!!!

Deadline extended to October 15th!

PAPER/ABSTRACT DEADLINE ALREADY END OF THIS WEEK! ELLIS Machine Learning for Molecules workshop: moleculediscovery.github.io/workshop2025/ DON'T MISS THE DEADLINE: short papers or extended abstracts welcome!

ELLIS ML4Molecules workshop 2025 ** Call for papers** is out: moleculediscovery.github.io/workshop2025/

Is Bluesky the actual dead Internet??

It's happening again!!! ML4Molecules workshop 2025. within the #ELLIS Unconference, preceding #EurIPS. More infos: moleculediscovery.github.io/workshop2025/

Happy that IBM uses proper MLPs, i.e. self-normalizing networks, in their Flowstate model! ;) P: arxiv.org/abs/2508.05287

Another win for xLSTM

It just struck me that the ancient Greeks chose their twelve Olympian gods with gender parity..

We Austrians are fully aware that we are a democratic country now, but we still sneak in pictures of our monarchs... :)

Controversial posts are downranked on Blue sky???? Oh c'mon...

Machine Learning-Driven Optimization of Specific, Compact, and Efficient Base Editors via Single-Round Diversification New base editors designed and optimized with ML! Almost all ML-designed ones active in the lab tests!! P: www.biorxiv.org/content/10.1...

Devastating blow for GNNs/MPNNs for chemistry and small molecules: All of them are not statistically better than simple ECFP . Only our CLAMP model does the job ;) P: arxiv.org/abs/2508.06199

Just in: GPT-5 achieves AGI in chemical sciences!!1!!1! Actually, NO! .... struggles with generating 2D graphs from SMILES.

Great idea for a dataset and task! Thanks for using and assessing out Prot-xLSTM

We are soooo proud. Our European-developed TiRex is leading the field—significantly ahead of U.S. competitors like Amazon, Datadog, Salesforce, and Google, as well as Chinese models from companies such as Alibaba.

Ever though you could get a 35 million parameter time series state-of-the art foundation model that you can run on embedded hardware? Thanks to @hochreitersepp.bsky.social and his team at NXAI, you can. Amazing work! Paper: arxiv.org/abs/2505.23719 Code: github.com/NX-AI/tirex

Recommended read for the weekend: Sepp Hochreiter's book on AI! Lots of fun anecdotes and easily accessible basics on AI! www.beneventopublishing.com/ecowing/prod...

Happy to introduce 🔥LaM-SLidE🔥! We show how trajectories of spatial dynamical systems can be modeled in latent space by --> leveraging IDENTIFIERS. 📚Paper: arxiv.org/abs/2502.12128 💻Code: github.com/ml-jku/LaM-S... 📝Blog: ml-jku.github.io/LaM-SLidE/ 1/n

Latent Space Modeling of Spatial Dynamical Systems via Linked Entities LATENT DIFFUSION and GRAPH NEURAL NETWORKS finally combined!! Best model for molecular dynamics of small molecules!!! Paper: arxiv.org/abs/2502.121... Blog: ml-jku.github.io/LaM-SLidE/

Join the tutorial on xLSTM!!

Talking at CAIML Symposium today "A New Generation of Foundation Models Based on xLSTM" Slides available here: cloud.ml.jku.at/s/fLtjm5GKQS... caiml.org/news/194/

Transformer-dot-com bubble.

In-context learning for molecules. HuggingFace App. Try it out!!!

TENURE TRACK PROFESSORSHIP in Reinforcement Learning announced at Johannes Kepler University Linz. Three other ML/AI tenure tracks also open. www.jku.at/en/the-jku/w...

Talking about AI systems and their slow uptake into healthcare systems and clinical practice today at dHealth: dHealth 2025 conference: dhealth.at/programme/ Slides: cloud.ml.jku.at/s/sNs3Z2GD2C...

Leveraging Partial SMILES Validation Scheme for Enhanced Drug Design in Reinforcement Learning Frameworks Uncomplete SMILES strings already assessed during autoregressive generation. Decreases amount of incorrect molecules. P: arxiv.org/abs/2505.00530

May the 4th be with you!

MHNfs: Prompting In-Context Bioactivity Predictions for Low-Data Drug Discovery Few-shot models for molecules now easily accessible via web application. Predictions via prompting SMILES P: pubs.acs.org/doi/10.1021/...

Softpick: No Attention Sink, No Massive Activations with Rectified Softmax Work claims that asing softpick instead of softmax in LLM training removes attention sinks and massive activations. Run with 0.37B parameter LLM similar to normal attention P: arxiv.org/abs/2504.20966

Come to Austria and work in AI for Life Sciences!!

Knowledge Distillation for Molecular Property Prediction: A Scalability Analysis Distillation does not only work for LLMs, but also for activity/property prediction models for molecules. P: advanced.onlinelibrary.wiley.com/doi/full/10....

Augmented and Programmatically Optimized LLM Prompts Reduce Chemical Hallucinations Topological polar surface area (TPSA) predicted by an LLM. Fewer confabulations with a RAG systems plus some additional safeguards. P: doi.org/10.1021/acs....

1/11 Excited to present our latest work "Scalable Discrete Diffusion Samplers: Combinatorial Optimization and Statistical Physics" at #ICLR2025 on Fri 25 Apr at 10 am! #CombinatorialOptimization #StatisticalPhysics #DiffusionModels