
Tzu-Mao Li
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2020 – today
- 2020
- [j11]Tzu-Mao Li, Michal Lukác, Michaël Gharbi, Jonathan Ragan-Kelley:
Differentiable vector graphics rasterization for editing and learning. ACM Trans. Graph. 39(6): 193:1-193:15 (2020) - [j10]Sai Praveen Bangaru, Tzu-Mao Li, Frédo Durand:
Unbiased warped-area sampling for differentiable rendering. ACM Trans. Graph. 39(6): 245:1-245:18 (2020) - [c3]Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, Frédo Durand:
DiffTaichi: Differentiable Programming for Physical Simulation. ICLR 2020 - [c2]Shuang Zhao, Wenzel Jakob, Tzu-Mao Li:
Physics-based differentiable rendering: from theory to implementation. SIGGRAPH Courses 2020: 14:1-14:30 - [i5]Gilbert Bernstein, Michael Mara, Tzu-Mao Li, Dougal Maclaurin, Jonathan Ragan-Kelley:
Differentiating a Tensor Language. CoRR abs/2008.11256 (2020) - [i4]Luke Anderson, Andrew Adams, Karima Ma, Tzu-Mao Li, Jonathan Ragan-Kelley:
Learning to Schedule Halide Pipelines for the GPU. CoRR abs/2012.07145 (2020)
2010 – 2019
- 2019
- [j9]Andrew Adams, Karima Ma, Luke Anderson, Riyadh Baghdadi, Tzu-Mao Li, Michaël Gharbi, Benoit Steiner, Steven Johnson, Kayvon Fatahalian, Frédo Durand, Jonathan Ragan-Kelley:
Learning to optimize halide with tree search and random programs. ACM Trans. Graph. 38(4): 121:1-121:12 (2019) - [j8]Michaël Gharbi, Tzu-Mao Li, Miika Aittala, Jaakko Lehtinen, Frédo Durand:
Sample-based Monte Carlo denoising using a kernel-splatting network. ACM Trans. Graph. 38(4): 125:1-125:12 (2019) - [j7]Yuanming Hu, Tzu-Mao Li, Luke Anderson, Jonathan Ragan-Kelley, Frédo Durand:
Taichi: a language for high-performance computation on spatially sparse data structures. ACM Trans. Graph. 38(6): 201:1-201:16 (2019) - [c1]Dejan Azinovic, Tzu-Mao Li, Anton Kaplanyan, Matthias Nießner:
Inverse Path Tracing for Joint Material and Lighting Estimation. CVPR 2019: 2447-2456 - [i3]Dejan Azinovic, Tzu-Mao Li, Anton Kaplanyan, Matthias Nießner:
Inverse Path Tracing for Joint Material and Lighting Estimation. CoRR abs/1903.07145 (2019) - [i2]Tzu-Mao Li:
Differentiable Visual Computing. CoRR abs/1904.12228 (2019) - [i1]Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, Frédo Durand:
DiffTaichi: Differentiable Programming for Physical Simulation. CoRR abs/1910.00935 (2019) - 2018
- [j6]Tzu-Mao Li, Michaël Gharbi, Andrew Adams, Frédo Durand, Jonathan Ragan-Kelley:
Differentiable programming for image processing and deep learning in halide. ACM Trans. Graph. 37(4): 139:1-139:13 (2018) - [j5]Tzu-Mao Li, Miika Aittala, Frédo Durand, Jaakko Lehtinen:
Differentiable Monte Carlo ray tracing through edge sampling. ACM Trans. Graph. 37(6): 222:1-222:11 (2018) - 2017
- [j4]Luke Anderson, Tzu-Mao Li, Jaakko Lehtinen, Frédo Durand:
Aether: an embedded domain specific sampling language for Monte Carlo rendering. ACM Trans. Graph. 36(4): 99:1-99:16 (2017) - 2015
- [j3]Tzu-Mao Li, Jaakko Lehtinen, Ravi Ramamoorthi, Wenzel Jakob, Frédo Durand:
Anisotropic Gaussian mutations for metropolis light transport through Hessian-Hamiltonian dynamics. ACM Trans. Graph. 34(6): 209:1-209:13 (2015) - [j2]Yu-Ting Wu
, Tzu-Mao Li, Yu-Hsun Lin, Yung-Yu Chuang:
Dual-Matrix Sampling for Scalable Translucent Material Rendering. IEEE Trans. Vis. Comput. Graph. 21(3): 363-374 (2015) - 2012
- [j1]Tzu-Mao Li, Yu-Ting Wu
, Yung-Yu Chuang
:
SURE-based optimization for adaptive sampling and reconstruction. ACM Trans. Graph. 31(6): 194:1-194:9 (2012)
Coauthor Index

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