4 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2022
CIGMO: Categorical invariant representations in a deep generative framework
Haruo Hosoya
Data of general object images have two most common structures: (1) each object of a given shape can be rendered in multiple different views, and (2) shapes of objects can be catego…
cs.LG2018
Group-based Learning of Disentangled Representations with Generalizability for Novel Contents
Haruo Hosoya
Sensory data are often comprised of independent content and transformation factors. For example, face images may have shapes as content and poses as transformation. To infer separa…
cs.PL2007★ 4 cited
Towards Practical Typechecking for Macro Tree Transducers
Alain Frisch, Haruo Hosoya
Macro tree transducers (mtt) are an important model that both covers many useful XML transformations and allows decidable exact typechecking. This paper reports our first step towa…