TRIE benchmarks stochastic PDE surrogates on two chaotic SPDEs, finding generative models best match long-term statistics and uncertainty while latent versions cut inference time by 12x.
Unreliable uncertainty estimates with monte carlo dropout.arXiv preprint arXiv:2512.14851,
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TRIE: An Evaluation Framework for Stochastic PDE Surrogates
TRIE benchmarks stochastic PDE surrogates on two chaotic SPDEs, finding generative models best match long-term statistics and uncertainty while latent versions cut inference time by 12x.
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General Incomplete Multimodal Learning via Dynamic Quality Perception
A unified multimodal learning framework models modality degradation as a continuous variable and uses a noise-aware quality estimator to adaptively weight fused representations under both intra- and inter-modality missingness.