Sakai, H., Freude, C., Auzinger, T., Hahn, D., & Wimmer, M. (2024). A Statistical Approach to Monte Carlo Denoising. In SA ’24: SIGGRAPH Asia 2024 Conference Papers. SA ’24: SIGGRAPH Asia 2024, Tokyo, Japan. Association for Computing Machinery. https://doi.org/10.1145/3680528.3687591 ( reposiTUm)

Freude, C., Sakai, H., Zsolnai-Fehér, K., & Wimmer, M. (2023). Sampling-Distribution-Based Evaluation for Monte Carlo Rendering. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 119–130). Scitepress. https://doi.org/10.34726/3841 ( reposiTUm)

Cornel, D., Sakai, H., Luksch, C., & Wimmer, M. (2017). Forced Random Sampling: fast generation of importance-guided blue-noise samples. In The Visual Computer (pp. 833–843). The Visual Computer. http://hdl.handle.net/20.500.12708/56977 ( reposiTUm)

Zargamy, A., Sakai, H., Oberwandling, G., & Ganhör, R. (2013). Fußgängernavigation im urbanen Raum - Designvorschlag. In Mensch & Computer 2013 - Tagungsband (pp. 365–368). Oldenbourg Wissenschaftsverlag. https://doi.org/10.1524/9783486781229.365 ( reposiTUm)

Sakai, H. (2015). Exploiting a priori information for filtering Mone Carlo renderings [Diploma Thesis, Technische Universität Wien]. reposiTUm. http://hdl.handle.net/20.500.12708/79782 ( reposiTUm)