Lecture 19: Variance Reduction (CMU 15-462/662) An overview various variance reduction techniques for Monte Carlo rendering, covering bidirectional path tracing, Metropolis-Hastings algorithm, MIS, stratified Sampling, low-discrepancy sampling, blue noise, photon mapping, and finite element radiosity
# In other words, without `call_soon_threadsafe`, a watcher
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Ports: Three Thunderbolt 5 (USB-C) ports, HDMI port, SDXC card slot, MagSafe 3 charging port, and a headphone jack
If I were to evade AIGC detection, the only ideas I have are fine-tuning an LLM on massive human text or building a giant rule-based lookup table to disrupt SVM-matched features. But obviously, that’s beyond this article. Not sure if it’d work either. Or maybe there are better ways—left as an exercise. Prove it yourself.