
ML Group, TU Berlin
72 posts

ML Group, TU Berlin
@ml_tuberlin
This is the Machine Learning Group of Prof. Klaus-Robert Müller @TUBerlin. Proud part of @bifoldberlin.




If two models are more similar to each other than a third on ImageNet, will this hold for medical/ satellite images? Our preprint analyzes how vision model similarities generalize across datasets, the factors that influence them, and their link to downstream task behavior. 🧵1/7

🎉 Thrilled to announce that our paper MambaLRP has been accepted at #NeurIPS2024! Explain your Mamba models in a faithful, efficient, and effective way! 🐍 Huge thanks to @EberleOliver, Grégoire Montavon, and Klaus-Robert Müller @bifoldberlin, @ml_tuberlin , @GoogleDeepMind,

Our work on historical insights at scale using machine learning is now out in @ScienceAdvances! Very proud of this team effort, bridging disciplines and institutions—@MPIWG @TUBerlin @bifoldberlin @ml_tuberlin 📜science.org/doi/10.1126/sc…

Which tasks benefit the most from aligning vision models with human perceptual judgments? In our most recent NeurIPS paper we pin down the downstream tasks where perceptual alignment yields the strongest increases in performance. More in the thread below 👇

#Job for #PhDCandidates: Develope and implement #XAI methods for ML models in Quantum Chemistry. BIFOLD is seeking a Research Associate in #ML for a project supervised by Dr. Stefan Chmiela and Dr. Shinichi Nakajima. Apply by 7th Nov '24 linkedin.com/jobs/view/4047… @ml_tuberlin

Couldn't have asked for better timing #NobelPrize Our new work on 'Molecular Simulations with a Pretrained Neural Network and Universal Pairwise Force Fields' is now out on @ChemRxiv! #MachineLearning #compchem






The results of the ☕️TEA Challenge 2023 and subsequent one-year investigations are now available as @ChemRxiv preprints in two parts👇1/3

✨ Our xMIL paper has been accepted at #NeurIPS2024 ✨ arXiv preprint: arxiv.org/abs/2406.04280

Really excited to share what we’ve been working on for the past 12 months during my time @GoogleDeepMind! We came up with an approach that can distill the hierarchical structure of human conceptual knowledge into vision foundation models via a surrogate teacher model. More below!


Greatful to be published @TmlrOrg. Thanks to @nstrodt and @jvielhaben for their support. @bifoldberlin @ml_tuberlin @FraunhoferHHI

🥳Many congratulations to Parastoo Semnani, member of the BIFOLD Graduate School, who won the "Best Poster Presentation"-Award at the 27th Canadian Symposium on Catalysis (CSC 2024) in Sherbrooke.

🚨 Preprint! Our #NAACL24 paper analyzes semantic textual similarity to unveil #LLM strategies via second-order BiLRP explanations. Preprint: arxiv.org/abs/2405.06604 Code: github.com/alevas/xai-sim… #ExplainableAI #NLP @AlexVsl2 @bifoldberlin @ml_tuberlin @TUBerlin @naaclmeeting


