Tzu-Mao Li
Most Recent Affiliation(s):
- MIT, Computer Science and Artificial Intelligence Laboratory (CSAIL), Postdoctoral Researcher
Location:
- Cambridge, Massachusetts, United States of America
Learning Category: Jury Member:
Award(s):
Experience(s):
Learning Category: Presentation(s):
![Acting as Inverse Inverse Planning](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Chandra_Acting-as-Inverse-Inverse-Planning-150x150.jpg)
Type: [Technical Papers]
Acting as Inverse Inverse Planning Presenter(s): [Chandra] [Li] [Tenenbaum] [Ragan-Kelley]
[SIGGRAPH 2023]
![Parameter-space ReSTIR for Differentiable and Inverse Rendering](https://history.siggraph.org/wp-content/uploads/2024/02/2023-Tech-Papers-Chang_Parameter-space-ReSTIR-for-Differentiable-and-Inverse-Rendering-150x150.jpg)
Type: [Technical Papers]
Parameter-space ReSTIR for Differentiable and Inverse Rendering Presenter(s): [Chang] [Sivaram] [Nowrouzezahrai] [Hachisuka] [Ramamoorthi] [Li]
[SIGGRAPH 2023]
![Systematically differentiating parametric discontinuities](https://history.siggraph.org/wp-content/uploads/2023/06/2021-Technical-Papers-Bangaru_Systematically-Differentiating-Parametric-Discontinuities-150x150.jpg)
Type: [Technical Papers]
Systematically differentiating parametric discontinuities Presenter(s): [Bangaru] [Michel] [Mu] [Bernstein] [Li] [Ragan-Kelley]
[SIGGRAPH 2021]
![Learning to optimize halide with tree search and random programs](https://history.siggraph.org/wp-content/uploads/2023/01/2019-Technical-Papers-Adams_Learning-to-Optimize-Halide-with-Tree-Search-and-Random-Programs-150x150.jpg)
Type: [Technical Papers]
Learning to optimize halide with tree search and random programs Presenter(s): [Adams] [Ma] [Anderson] [Baghdadi] [Li] [Gharbi] [Steiner] [Johnson] [Fatahalian] [Durand] [Ragan-Kelley]
[SIGGRAPH 2019]
![Sample-based Monte Carlo denoising using a kernel-splatting network](https://history.siggraph.org/wp-content/uploads/2023/01/2019-Technical-Papers-Gharbi_Sample-based-Monte-Carlo-Denoising-using-a-Kernel-Splatting-Network-150x150.jpg)
Type: [Technical Papers]
Sample-based Monte Carlo denoising using a kernel-splatting network Presenter(s): [Gharbi] [Li] [Aittala] [Lehtinen] [Durand]
[SIGGRAPH 2019]
Role(s):
- Awardee
- Course Presenter
- Studio (SIGGRAPH Lab) Presenter
- Technical Paper Presenter
- Technical Papers Jury Member
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