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We propose neural control variates (NCV) for unbiased variance reduction in parametric Monte Carlo integration.
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Understanding the Difficulty of Training Deep Feedforward Neural Networks. In Proc. 13th International Conference on Artificial Intelligence and Statistics (May 13–15). JMLR.org, 249–256
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Deep Scattering: Rendering Atmospheric Clouds with Radiance-Predicting Neural Networks
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Practical Path Guiding for Efficient Light-Transport Simulation
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5D Covariance Tracing for Efficient Defocus and Motion Blur
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Global Illumination with Radiance Regression Functions
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A Family of Nonparametric Density Estimation Algorithms
Esteban Tabak and Cristina V. Turner. 2013 · 2013
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NICE: Non-linear Independent Components Estimation
Laurent Dinh, David Krueger, and Yoshua Bengio. 2014 · 2014
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Adam: A Method for Stochastic Optimization
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Learning Light Transport the Reinforced Way. In Monte Carlo and Quasi-Monte Carlo Methods , Art B. Owen and Peter W. Glynn (Eds.). Springer International Publishing, 181–195
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Glow: Generative Flow with Invertible 1x1 Convolutions
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Efficient Metropolis Path Sampling for Material Editing and Re-rendering. In Pacific Graphics Short Papers , Hongbo Fu, Abhijeet Ghosh, and Johannes Kopf (Eds.). The Eurographics Association
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Integral formulations of volumetric transmittance
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Volume Path Guiding Based on Zero-Variance Random Walk Theory
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Deep-learning the Latent Space of Light Transport
Pedro Hermosilla, Sebastian Maisch, Tobias Ritschel, and Timo Ropinski. 2019 · 2019
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Optimal Multiple Importance Sampling
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Neural Volumes: Learning Dynamic Renderable Volumes from Images
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Deep Appearance Maps. In The IEEE International Conference on Computer Vision (ICCV)
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Deep Reflectance Fields: High-quality Facial Reflectance Field Inference from Color Gradient Illumination
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“Practical Path Guiding” in Production. In ACM SIGGRAPH Courses: Path Guiding in Production, Chapter 10 . ACM, New York, NY, USA, 18:1–18:77
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Neural Importance Sampling
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Deferred Neural Rendering: Image Synthesis Using Neural Textures
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A Learned Shape-Adaptive Subsurface Scattering Model
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Neural Control Variates for Variance Reduction
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Learning to Importance Sample in Primary Sample Space
Quan Zheng and Matthias Zwicker. 2019 · 2019
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