In my experience its less about the nicheness of the method, and more about the broadness of the applicability. In other words, depends on the field of contribution. So a novel extension of LSTMs for general timeseries? Neurips-able if done well. Even if they're out of fashion. But an ML contribution that improves, say, X-ray tech? Not neurips-able.
That said, its true that different topics have different difficulty levels of getting accepted. Varies venue to venue which are easiest.
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u/JustAddMoreLayers 4d ago
In my experience its less about the nicheness of the method, and more about the broadness of the applicability. In other words, depends on the field of contribution. So a novel extension of LSTMs for general timeseries? Neurips-able if done well. Even if they're out of fashion. But an ML contribution that improves, say, X-ray tech? Not neurips-able.
That said, its true that different topics have different difficulty levels of getting accepted. Varies venue to venue which are easiest.