What an amazing release 👏 so many new and immensely useful features! 🤩

Rendering nerds! Check out our latest work "Vector-Valued Monte Carlo Integration Using Ratio Control Variates" that has just gotten the best paper award at SIGGRAPH 2025. This paper presents a method that reduces variance of a wide range of rendering and diff. rendering tasks with negligible cost.

The latest development version of Dr.Jit now provides built-in support for evaluating and training MLPs (including fusing them into rendering workloads). They compile to efficient Tensor Core operations via NVIDIA's Cooperative Vector extension. Details: drjit.readthedocs.io/en/latest/nn...

🚀 The source code for our #SIGGRAPH2025 paper "Practical Inverse Rendering of Textured and Translucent Appearance" is now available! 🔗 GitHub: github.com/google/pract...

Excited to finally share Philippe's amazing work that he did with our team at Google!

3D Gaussian splatting relies on depth-sorting of splats, which is costly and prone to artifacts (e.g., "popping"). In our latest work, "StochasticSplats", we replace sorted alpha blending by stochastic transparency, an unbiased Monte Carlo estimator from the real-time rendering literature.

(2/2) 🏆 Our invited speakers for February to April, 2025 includes: Dorian Chan, @axelparis.bsky.social, ZHEN XU, ezgi ozyilkan, Zhaocheng Liu, @deliovicini.bsky.social, Qi Guo, @niladridutt.bsky.social, Akshat Dave, Ethan Tseng, Ziyang Chen. 👉 For more details: complightlab.com/outreach

We are excited to present a SIGGRAPH Asia paper exploring a new application of inverse rendering to Tomographic Volumetric Additive Manufacturing (TVAM), a new light-based 3D printing technology that can print objects in less than a minute.

Super exciting to see these new versions finally being released. it's amazing how far Mitsuba & Dr.Jit have come!