Jonas Fischer

Research group leader @ Max Planck Institute for Informatics | Interested in ML, Stats, Data Mining, and everything that connects them.

[Explainable Machine Learning @ExplainableML]

📢 Fully funded PhD @ Helmholtz Munich + TUM
We're hiring PhD students to build trustworthy AI systems for science: explainable AI, VLMs, reliable adaptation, agentic workflows.
⏰ Priority deadline 10 Aug 2026. Application details below 👇

[Sukrut Rao @sukrutrao]

Have ideas for building and scaling interpretability methods?

Submit to the Explainable Computer Vision Workshop (eXCV) taking place at #ECCV2026! This year, the theme is the role of XAI in the era of foundation models.

@eccvconf

[Michael Hahn @mhahn29]

We have 1-2 more extra spots due to new funding -- apply by end of April!

[Jan Eric Lenssen @janericlenssen]

Can 3D scenes be represented by and rendered from a set of compressed tokens?

It turns out they can and it pairs very well with generative rendering to handle uncertainty!

Make sure to check out @Mohamma68780050's recent work Scenetok, accepted at #CVPR2026.

Links below.

[Jonas Fischer @JonasFischerML]

@nobolly Increadibly beautiful!

[Fawaz Sammani @fawaz_sammani]

Our paper “CLIP-Free, Label-Free, Unsupervised Concept Bottleneck Models” has been accepted to #CVPR2026 (Findings). This is one of my strongest PhD works, but at the same time, the most unluckiest. Anyways, Im happy to see its out now! #xai

Paper: https://t.co/vgG9J2eW6X

[Chris Olah @ch402]

We're hiring ~10 research engineers on the Interpretability team at Anthropic. If you're a seasoned ML infra engineer who's excited about understanding what's happening inside frontier models, we'd love to hear from you.

(No prior interp experience needed!)

[Jonas Fischer @JonasFischerML]

@AdaGorgun @fawaz_sammani Another great work from the lab at ICLR in Rio 🔥

[Jonas Fischer @JonasFischerML]

@NhiPham49 @AJesslen @AdamKortylewski Great to see this fantastic work appear at ICLR in Rio 🔥

[Nhi Pham @NhiPham49]

Huge thanks to my great co-author @AJesslen, and my three amazing advisors Bernt Schiele, @AdamKortylewski*, and @JonasFischerML*! (*equal advisorship)
📄 Paper: https://t.co/Sf1PwWNMYj
🌐 Project: https://t.co/FP2lIxbQxL
💻 Code: https://t.co/tXBI94CcQG
#ICLR2026 #XAI #3D

[Ada Görgün @AdaGorgun]

Huge thanks to my fantastic co-authors @fawaz_sammani (equal contribution), Nikos Deligiannis, Bernt Schiele, and @JonasFischerML ! Paper: https://t.co/y6nEdfRSao Page: https://t.co/QViROAdoSL: https://t.co/24NnOUjMOo #ICLR #ICLR2026 #Diffusion #DiffusionModels #XAI📷

[Nhi Pham @NhiPham49]

Robust classifiers are great. Interpretable models are great. But why do we still have to choose between the two?
🎉 Excited to share our paper "Interpretable 3D Neural Object Volumes for Robust Conceptual Reasoning" has been accepted to #ICLR2026 @iclr_conf !

[Explainable Machine Learning @ExplainableML]

🎓PhD application season @ExplainableML is back!

This year, we’re hiring ONLY through the ELLIS Program and the MCML Program: two fantastic communities shaping the future of AI and ML.

📌Please don’t forget to denote Prof. Dr. Zeynep Akata as one of your preferred supervisors!
👉 Link to ELLIS (https://t.co/TyRVozyjX3) and MCML (https://t.co/gE1sqSuEZf)

[Zeynep Akata @zeynepakata]

We are looking for PhD students. Please apply through the @ELLISforEurope and @MunichCenterML PhD programs!

[Naomi Saphra @nsaphra]

I’m recruiting PhD students for 2026! If you are interested in robustness, training dynamics, interpretability for scientific understanding, or the science of LLM analysis you should apply. BU is building a huge LLM analysis/interp group and you’ll be joining at the ground floor.

[Thomas Wimmer @wimmer_th]

Super excited to introduce

✨ AnyUp: Universal Feature Upsampling 🔎

Upsample any feature - really any feature - with the same upsampler, no need for cumbersome retraining.
SOTA feature upsampling results while being feature-agnostic at inference time.

[Sukrut Rao @sukrutrao]

Are you an XAI researcher attending #ICCV2025? Submit your recently published work — at CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, AAAI etc. — to the eXCV Workshop for the opportunity to further showcase your work! Published papers can be submitted as is, no rewriting necessary.

[Nina Shvetsova @ninashv__]

🚀 UTD is now fully released!
Code ✅ Models ✅ 2M video descriptions ✅ Debiased splits for 12 datasets ✅
Everything you need to benchmark video models more fairly is now public:
🔗 https://t.co/rA88ztIZJs
🎥 Let’s make video understanding actually about video understanding.

[Kosta Derpanis (sabbatical in Zurich) @CSProfKGD]

We've all been there 🤓

#DeepLearning

[tender @tenderizzation]

when you rely on data augmentation because your model doesn’t have scale equivariance built-in