Real data is noisy but HiPPO assumes it's clean. Our UnHiPPO initialization resists noise with implicit Kalman filtering and makes SSMs robust without architecture changes.
Learn more at our #ICML poster: Thu 11am E-2409
Paper: openreview.net/forum?id=U8G...
Code: github.com/martenlienen...
I am truly excited to share our latest work with @mscherbela.bsky.social, Philipp Grohs, and @guennemann on "Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure Problems"!
arxiv.org/abs/2504.06087
Excited to announce our #ICLR2025 spotlight work deriving the first exact certificates for neural networks against label poisoning 🎉. Joint work with @maha-saba.bsky.social, Stephan Günnemann & Debarghya Ghoshdastidar. For details, check out the thread below👇 or our paper arxiv.org/abs/2412.00537.
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=HRk...
Happy to chat!
Super happy & honored that our work on certifying NNs against poisoning won the Best Paper Award at AdvML-Frontiers@ #NeurIPS2024. Come by our poster 10:40am-12&4-5pm (or talk) today :)
Joint work w/ Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar & Stephan Günnemann
L: arxiv.org/pdf/2407.10867
We present finite-range embeddings (FiRE), a novel wave function ansatz for accurate large-scale ab-initio electronic structure calculations. Compared to contemporary neural-network wave functions, Fi...
Machine learning models are highly vulnerable to label flipping, i.e., the adversarial modification (poisoning) of training labels to compromise performance. Thus, deriving robustness certificates is ...
🎉Excited to announce our #ICLR2025 Spotlight!
🚀 @lukasgosch.bsky.social and I will be presenting our paper on the first exact certificate against label poisoning for neural nets and graph neural nets. Joint work with Stephan Guennemann and Debarghya Ghoshdastidar.
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