Dominik Fuchsgruber

PhD Student @TU_Muenchen | Uncertainty Estimation, Spatio-Temporal Learning

[Lukas Gosch @lukgosch]

Very happy to present our work on a principled robustness evaluation of graph transformers at #ICLR2026! You can talk to us at tomorrow's poster session from 10:30 am to 1 pm in Pavilion 3 - #816. Joint work with Philipp Foth, @geisler_si, @SchwinnLeo, and @guennemann.

[Dominik Fuchsgruber @dfuchsgruber]

Check out our latest work on using a task-dependent latent structure to improve LLM generations and uncertainty!

[Tim Tomov @timtomov]

Are LLM outputs just language?

We often don’t know what the answer to a question will be - but we do know its structure. Numbers, lists, sets, ...

Our framework models outputs in their underlying structure for better answers + uncertainty.

w/ @dfuchsgruber @guennemann [1/4]🧵

[Tim Tomov @timtomov]

Are LLM outputs just language?

We often don’t know what the answer to a question will be - but we do know its structure. Numbers, lists, sets, ...

Our framework models outputs in their underlying structure for better answers + uncertainty.

w/ @dfuchsgruber @guennemann [1/4]🧵

[Lukas Gosch @lukgosch]

Excited to announce our #ICLR2025 spotlight work deriving the first exact certificates for neural networks against label poisoning 🎉. Joint work w/ @maha81193, @guennemann & Debarghya. For more details check out the thread below👇 or check out our paper https://t.co/MPX1EqDCPG.

[Amine Ketata @amine_ketata]

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 @n_gao96, @TomWollschlager, @j_m_sommer, and @guennemann.

🧵 1/

[Nicholas Gao @n_gao96]

I am truly excited to share our latest work with @MScherbela, @GrohsPhilipp, and @guennemann on "Accurate Ab-initio Neural-network Solutions to
Large-Scale Electronic Structure Problems"!

https://t.co/By8CetKwHU

[Eike Eberhard @ESEberhard]

The paper of my final "pure" physics project just got published in @NanoLetters
https://t.co/vf1AciNaru

joint work with Ludwig Burger, @ceslopast, Hamid Seyed-Allaei @GiovanniGiunt20 and Ulrich Gerland

[Simon Geisler @geisler_si]

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 @guennemann's lab & @GoogleAI, w/ @cais support

Here's how we did it. 🧵

[Leo Schwinn @SchwinnLeo]

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?🧵
@guennemann @gauthier_gidel

[Stephan Günnemann @guennemann]

Congrats to my amazing PhD students: We have 9 papers accepted at #ICLR2025. Reliability, AI4Science, graphs, LLMs, and more (https://t.co/O3f86agVaN).

And if you follow the recent discussions about AI efficiency, you might like our blog and webinars (https://t.co/MsohgAJRUZ).

[Lukas Gosch @lukgosch]

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/@maha81193, Debarghya Ghoshdastidar & @guennemann

L: https://t.co/PrZi2nlUtY

[Arthur Kosmala @ArthurK48147]

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/ @geisler_si @dan1elherbst @guennemann.

📎 https://t.co/wzX5M67oPY

📆 Dec 13, 11am, #4608

[Dominik Fuchsgruber @dfuchsgruber]

Pay our poster a visit if you want to know more!

[Dominik Fuchsgruber @dfuchsgruber]

Excited to present our spotlight paper on uncertainty for GNNs at #NeurIPS!

📝Paper: https://t.co/YW8B7tXqoo
📆Come by our poster on Dec 12th at 11am!

Thanks to my amazing collaborators @TomWollschlager and @guennemann!

[Dominik Fuchsgruber @dfuchsgruber]

🏃‍♂️Our model can applied both post-hoc at negligible cost to many popular GNNs!

🔦We also establish a connection to evidential learning that drastically improves the robustness to distribution shifts in terms of accuracy.

[Nicholas Gao @n_gao96]

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: https://t.co/X54t2hhfZs

Happy to chat!

[Sirine Ayadi @sirine_ayadi1]

This week, we will present our recent #NeurIPS2024 paper. 

📎 Paper: https://t.co/92UJBKn4WZ 
📆 Make sure to visit our poster #2600 on Fri, 13 December at 11 am! 

Joint work with my amazing mentors @leon_het @j_m_sommer @fabian_theis @guennemann

[Marcel Kollovieh @MarcelKollovieh]

Next week, I'll present our recent paper at NeurIPS 2024 in Vancouver.

Many thanks to my amazing collaborators @Bertrand_Charp, @DanielZuegner , and @guennemann!