most citedNeural Parametric Mixtures for Path Guiding

15 citations · 22 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

BEACON: Bayesian Optimal Stopping for Efficient LLM Sampling

Guangya Wan, Zixin Stephen Xu, Sasa Zorc +4

Sampling multiple responses is a common way to improve LLM output quality, but it comes at the cost of additional computation. The key challenge is deciding when to stop generating…

cs.GR20252 cited

Hypothesis Testing for Progressive Kernel Estimation and VCM Framework

Zehui Lin, Chenxiao Hu, Jinzhu Jia +1

Identifying an appropriate radius for unbiased kernel estimation is crucial for the efficiency of radiance estimation. However, determining both the radius and unbiasedness still f…

cs.GR202515 cited

Neural Parametric Mixtures for Path Guiding

Honghao Dong, Guoping Wang, Sheng Li

Previous path guiding techniques typically rely on spatial subdivision structures to approximate directional target distributions, which may cause failure to capture spatio-directi…

cs.GR20253 cited

Proxy Tracing: Unbiased Reciprocal Estimation for Optimized Sampling in BDPT

Fujia Su, Bingxuan Li, Qingyang Yin +2

Robust light transport algorithms, particularly bidirectional path tracing (BDPT), face significant challenges when dealing with specular or highly glossy involved paths. BDPT cons…

cs.GR20252 cited

Visual Acuity Consistent Foveated Rendering towards Retinal Resolution

Zhi Zhang, Meng Gai, Sheng Li

Prior foveated rendering methods often suffer from a limitation where the shading load escalates with increasing display resolution, leading to decreased efficiency, particularly w…