Classes
Publications
- A Unified Manifold Framework for Efficient BRDF Sampling based on Parametric Mixture Models2018 | Faculty of Mathematics and Physics
- Machine Learning and Rendering2018 | Faculty of Mathematics and Physics
- Product Importance Sampling for Light Transport Path Guiding2016 | Faculty of Mathematics and Physics
- On-line Learning of Parametric Mixture Models for Light Transport Simulation2014 | Faculty of Mathematics and Physics
- Survey and Evaluation of Neural 3D Shape Classification Approaches2021 | Faculty of Mathematics and Physics, Central Library of Charles University
- A Gradient-Based Framework for 3D Print Appearance Optimization2021 | Faculty of Mathematics and Physics, Central Library of Charles University
- A Fitted Radiance and Attenuation Model for Realistic Atmospheres2021 | Faculty of Mathematics and Physics, Central Library of Charles University
- Robust and practical measurement of volume transport parameters in solid photo-polymer materials for 3D printing2021 | Faculty of Mathematics and Physics
- Variance-Aware Path Guiding2020 | Faculty of Mathematics and Physics
- Optimal Multiple Importance Sampling2019 | Faculty of Mathematics and Physics
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