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Showing papers from Swiss Federal Institute of Technology Show all papers

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NeurIPS 2026ETH ZurichETHZIBM Research EuropeSwiss Federal Institute of TechnPhysics-informed ML & PDEs

Phaedra: Learning High-Fidelity Discrete Tokenization for the Physical Sciences

Levi Lingsch, Georgios Kissas, Johannes Jakubik, Siddhartha Mishra

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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medium 0/10
strict 0/5
67%Highly rated
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NeurIPS 2026ETH ZurichZhengzhouMBZUAISwiss Federal Institute of TechnEPFL - EPF LausanneVision-language models

Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study

Hao Dong, Hongzhao Li, Shupan Li, Muhammad Haris Khan and 2 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 0/5
67%Highly rated
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NeurIPS 2026U AmsterdamSwiss Data Science Center, ETH ZETH ZurichUniversity Of CambridgeSwiss Federal Institute of TechnSpatio-temporal forecasting

Long-Rollout Stability in AI Weather Models: A Quantitative Benchmark and Analysis

Fanny Lehmann, Firat Ozdemir, Yun Cheng, Torsten Hoefler and 3 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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lenient 2/5
medium 0/10
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78%Highly rated
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NeurIPS 2026Swiss Federal Institute of TechnETH ZürichETHZ - ETH ZurichETH ZurichMolecules & drug discovery

Breaking the Synthesis Barrier for AI-Designed DNA Libraries

PGLD optimizes synthesis-aware stochastic DNA libraries via policy gradients to bypass synthesis cost limits, enabling million-sequence libraries for antibody exploration at low cost.

Scott Sussex, Ema Borevković, Frederieke Lohmann, Ningning Chen and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 0/5