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2020 – today
- 2024
[j28]Bing Xu
, Tzu-Mao Li, Iliyan Georgiev, Trevor Hedstrom, Ravi Ramamoorthi:
Residual path integrals for re-rendering. Comput. Graph. Forum 43(4): i-x (2024)- [j27]Jesse Michel, Kevin Mu, Xuanda Yang, Sai Praveen Bangaru, Elias Rojas Collins, Gilbert Bernstein, Jonathan Ragan-Kelley, Michael Carbin, Tzu-Mao Li:
Distributions for Compositionally Differentiating Parametric Discontinuities. Proc. ACM Program. Lang. 8(OOPSLA1): 893-922 (2024) - [j26]Yash Belhe, Bing Xu, Sai Praveen Bangaru, Ravi Ramamoorthi, Tzu-Mao Li:
Importance Sampling BRDF Derivatives. ACM Trans. Graph. 43(3): 25:1-25:21 (2024) - [j25]Chuhao Chen, Yuze He, Tzu-Mao Li:
Temporally Stable Metropolis Light Transport Denoising using Recurrent Transformer Blocks. ACM Trans. Graph. 43(4): 123:1-123:14 (2024) - [j24]Haolin Lu, Wesley Chang, Trevor Hedstrom, Tzu-Mao Li:
Real-Time Path Guiding Using Bounding Voxel Sampling. ACM Trans. Graph. 43(4): 125:1-125:14 (2024) - [c16]Yun-Hsuan Lien, Ping-Chun Hsieh, Tzu-Mao Li, Yu-Shuen Wang:
Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning. ICML 2024 - [c15]Venkataram Edavamadathil Sivaram, Tzu-Mao Li, Ravi Ramamoorthi:
Neural Geometry Fields For Meshes. SIGGRAPH (Conference Paper Track) 2024: 29 - [c14]Wesley Chang, Xuanda Yang, Yash Belhe, Ravi Ramamoorthi, Tzu-Mao Li:
Spatiotemporal Bilateral Gradient Filtering for Inverse Rendering. SIGGRAPH Asia 2024: 70:1-70:11 - [c13]Ziyang Fu, Yash Belhe, Haolin Lu, Liwen Wu, Bing Xu, Tzu-Mao Li:
BSDF importance sampling using a diffusion model. SIGGRAPH Asia 2024: 83:1-83:11 - [c12]Peiyu Xu, Sai Praveen Bangaru, Tzu-Mao Li, Shuang Zhao:
Markov-Chain Monte Carlo Sampling of Visibility Boundaries for Differentiable Rendering. SIGGRAPH Asia 2024: 118:1-118:11 - [i16]Kartik Chandra, Tzu-Mao Li, Rachit Nigam, Joshua B. Tenenbaum, Jonathan Ragan-Kelley:
WatChat: Explaining perplexing programs by debugging mental models. CoRR abs/2403.05334 (2024) - [i15]Bing Xu, Tzu-Mao Li, Iliyan Georgiev, Trevor Hedstrom, Ravi Ramamoorthi:
Residual path integrals for re-rendering. CoRR abs/2406.16302 (2024) - 2023
- [j23]Nithin Raghavan, Yan Xiao, Kai-En Lin, Tiancheng Sun, Sai Bi, Zexiang Xu, Tzu-Mao Li, Ravi Ramamoorthi:
Neural Free-Viewpoint Relighting for Glossy Indirect Illumination. Comput. Graph. Forum 42(4): i-x (2023) - [j22]Andrew Spielberg, Fangcheng Zhong, Konstantinos Rematas, Krishna Murthy Jatavallabhula, Cengiz Öztireli, Tzu-Mao Li, Derek Nowrouzezahrai:
Differentiable visual computing for inverse problems and machine learning. Nat. Mac. Intell. 5(11): 1189-1199 (2023) - [j21]Shiyang Jia, Stephanie Wang, Tzu-Mao Li, Albert Chern:
Physical Cyclic Animations. Proc. ACM Comput. Graph. Interact. Tech. 6(3): 45:1-45:18 (2023) - [j20]Peiyu Xu, Sai Praveen Bangaru, Tzu-Mao Li, Shuang Zhao:
Warped-Area Reparameterization of Differential Path Integrals. ACM Trans. Graph. 42(6): 213:1-213:18 (2023) - [j19]Yash Belhe, Michaël Gharbi, Matthew Fisher, Iliyan Georgiev, Ravi Ramamoorthi, Tzu-Mao Li:
Discontinuity-Aware 2D Neural Fields. ACM Trans. Graph. 42(6): 217:1-217:11 (2023) - [j18]Sai Praveen Bangaru, Lifan Wu, Tzu-Mao Li, Jacob Munkberg, Gilbert Bernstein, Jonathan Ragan-Kelley, Frédo Durand, Aaron E. Lefohn, Yong He:
SLANG.D: Fast, Modular and Differentiable Shader Programming. ACM Trans. Graph. 42(6): 264:1-264:28 (2023) - [j17]Kartik Chandra, Tzu-Mao Li, Joshua B. Tenenbaum, Jonathan Ragan-Kelley:
Storytelling as Inverse Inverse Planning. Top. Cogn. Sci. 16(1): 54-70 (2023) - [c11]Kartik Chandra, Tzu-Mao Li, Josh Tenenbaum, Jonathan Ragan-Kelley:
Storytelling as Inverse Inverse Planning. CogSci 2023 - [c10]Liwen Wu, Rui Zhu, Mustafa B. Yaldiz, Yinhao Zhu, Hong Cai, Janarbek Matai, Fatih Porikli, Tzu-Mao Li, Manmohan Chandraker, Ravi Ramamoorthi:
Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation. ICCV 2023: 3825-3835 - [c9]Kartik Chandra, Tony Chen, Tzu-Mao Li, Jonathan Ragan-Kelley, Josh Tenenbaum:
Inferring the Future by Imagining the Past. NeurIPS 2023 - [c8]Kartik Chandra, Tzu-Mao Li, Joshua B. Tenenbaum, Jonathan Ragan-Kelley:
Acting as Inverse Inverse Planning. SIGGRAPH (Conference Paper Track) 2023: 7:1-7:12 - [c7]Wesley Chang, Venkataram Sivaram, Derek Nowrouzezahrai, Toshiya Hachisuka, Ravi Ramamoorthi, Tzu-Mao Li:
Parameter-space ReSTIR for Differentiable and Inverse Rendering. SIGGRAPH (Conference Paper Track) 2023: 18:1-18:10 - [i14]Yash Belhe, Bing Xu, Sai Praveen Bangaru, Ravi Ramamoorthi, Tzu-Mao Li:
Importance Sampling BRDF Derivatives. CoRR abs/2304.04088 (2023) - [i13]Liwen Wu, Rui Zhu, Mustafa B. Yaldiz, Yinhao Zhu, Hong Cai, Janarbek Matai, Fatih Porikli, Tzu-Mao Li, Manmohan Chandraker, Ravi Ramamoorthi:
Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation. CoRR abs/2304.05669 (2023) - [i12]Kartik Chandra, Tzu-Mao Li, Josh Tenenbaum, Jonathan Ragan-Kelley:
Acting as Inverse Inverse Planning. CoRR abs/2305.16913 (2023) - [i11]Kartik Chandra, Tony Chen, Tzu-Mao Li, Jonathan Ragan-Kelley, Joshua B. Tenenbaum:
Inferring the Future by Imagining the Past. CoRR abs/2305.17195 (2023) - [i10]Nithin Raghavan, Yan Xiao, Kai-En Lin, Tiancheng Sun, Sai Bi, Zexiang Xu, Tzu-Mao Li, Ravi Ramamoorthi:
Neural Free-Viewpoint Relighting for Glossy Indirect Illumination. CoRR abs/2307.06335 (2023) - [i9]Andrew Spielberg, Fangcheng Zhong, Konstantinos Rematas, Krishna Murthy Jatavallabhula, Cengiz Öztireli, Tzu-Mao Li, Derek Nowrouzezahrai:
Differentiable Visual Computing for Inverse Problems and Machine Learning. CoRR abs/2312.04574 (2023) - 2022
- [j16]Tzu-Mao Li:
Differentiable Visual Computing: Challenges and Opportunities. IEEE Computer Graphics and Applications 42(2): 101-109 (2022) - [j15]Karima Ma, Michaël Gharbi, Andrew Adams, Shoaib Kamil, Tzu-Mao Li, Connelly Barnes, Jonathan Ragan-Kelley:
Searching for Fast Demosaicking Algorithms. ACM Trans. Graph. 41(5): 172:1-172:18 (2022) - [c6]Kartik Chandra, Tzu-Mao Li, Joshua B. Tenenbaum, Jonathan Ragan-Kelley:
Designing Perceptual Puzzles by Differentiating Probabilistic Programs. SIGGRAPH (Conference Paper Track) 2022: 21:1-21:9 - [c5]Sai Praveen Bangaru, Michaël Gharbi, Fujun Luan, Tzu-Mao Li, Kalyan Sunkavalli, Milos Hasan, Sai Bi, Zexiang Xu, Gilbert Bernstein, Frédo Durand:
Differentiable Rendering of Neural SDFs through Reparameterization. SIGGRAPH Asia 2022: 5:1-5:9 - [i8]Kartik Chandra, Tzu-Mao Li, Joshua B. Tenenbaum, Jonathan Ragan-Kelley:
Designing Perceptual Puzzles by Differentiating Probabilistic Programs. CoRR abs/2204.12301 (2022) - [i7]Sai Praveen Bangaru, Michaël Gharbi, Tzu-Mao Li, Fujun Luan, Kalyan Sunkavalli, Milos Hasan, Sai Bi, Zexiang Xu, Gilbert Bernstein, Frédo Durand:
Differentiable Rendering of Neural SDFs through Reparameterization. CoRR abs/2206.05344 (2022) - 2021
- [j14]Luke Anderson, Andrew Adams, Karima Ma, Tzu-Mao Li, Tian Jin, Jonathan Ragan-Kelley:
Efficient automatic scheduling of imaging and vision pipelines for the GPU. Proc. ACM Program. Lang. 5(OOPSLA): 1-28 (2021) - [j13]Sai Praveen Bangaru, Jesse Michel, Kevin Mu, Gilbert Bernstein, Tzu-Mao Li, Jonathan Ragan-Kelley:
Systematically differentiating parametric discontinuities. ACM Trans. Graph. 40(4): 107:1-107:18 (2021) - [j12]Yu-Chen Wang, Yu-Ting Wu, Tzu-Mao Li, Yung-Yu Chuang:
Learning to cluster for rendering with many lights. ACM Trans. Graph. 40(6): 277:1-277:10 (2021) - [c4]Connor Imes, Tzu-Mao Li, Mark Glines, Rishi Khan, John Paul Walters:
Distributed and Heterogeneous SAR Backprojection with Halide. HPEC 2021: 1-9 - [i6]Spandan Madan, Tomotake Sasaki, Tzu-Mao Li, Xavier Boix, Hanspeter Pfister:
Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers. CoRR abs/2106.16198 (2021) - 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 (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 (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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