1 citations · 5 across the 34 of their papers we have counts for
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cs.LG2026
Are We Overthinking One-Step Generation?
Woobin Park, Jaeyeon Kim, Yilun Du +2
Diffusion and flow matching are now dominant frameworks for generative modeling in continuous domains, but they typically require multiple network evaluations at inference. This ha…
cs.LG2026
Towards Multi-Source Domain Generalization for Sleep Staging with Noisy Labels
Kening Wang, Di Wen, Yufan Chen +6
Automatic sleep staging is a multimodal learning problem involving heterogeneous physiological signals such as EEG and EOG, which often suffer from domain shifts across institution…
cs.LG2024★ 1 cited
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
Kunyu Peng, Di Wen, Kailun Yang +6
In Open-Set Domain Generalization (OSDG), the model is exposed to both new variations of data appearance (domains) and open-set conditions, where both known and novel categories ar…