Tzu-Mao Li

According to our database, Tzu-Mao Li authored at least 40 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

WatChat: Explaining perplexing programs by debugging mental models.

Kartik Chandra, Tzu-Mao Li, Rachit Nigam, Joshua B. Tenenbaum, Jonathan Ragan-Kelley

CoRR, 2024

2023

Warped-Area Reparameterization of Differential Path Integrals.

Peiyu Xu, Sai Praveen Bangaru, Tzu-Mao Li, Shuang Zhao

ACM Trans. Graph., December, 2023

Discontinuity-Aware 2D Neural Fields.

Yash Belhe, Michaël Gharbi, Matthew Fisher, Iliyan Georgiev, Ravi Ramamoorthi, Tzu-Mao Li

ACM Trans. Graph., December, 2023

SLANG.D: Fast, Modular and Differentiable Shader Programming.

Sai Praveen Bangaru, Lifan Wu, Tzu-Mao Li, Jacob Munkberg, Gilbert Bernstein, Jonathan Ragan-Kelley, Frédo Durand, Aaron E. Lefohn, Yong He

ACM Trans. Graph., December, 2023

Differentiable visual computing for inverse problems and machine learning.

Andrew Spielberg, Fangcheng Zhong, Konstantinos Rematas, Krishna Murthy Jatavallabhula, Cengiz Öztireli, Tzu-Mao Li, Derek Nowrouzezahrai

Nat. Mac. Intell., October, 2023

Physical Cyclic Animations.

Shiyang Jia, Stephanie Wang, Tzu-Mao Li, Albert Chern

Proc. ACM Comput. Graph. Interact. Tech., August, 2023

Neural Free-Viewpoint Relighting for Glossy Indirect Illumination.

Nithin Raghavan, Yan Xiao, Kai-En Lin, Tiancheng Sun, Sai Bi, Zexiang Xu, Tzu-Mao Li, Ravi Ramamoorthi

Comput. Graph. Forum, July, 2023

Storytelling as <i>Inverse</i> Inverse Planning.

Kartik Chandra, Tzu-Mao Li, Joshua B. Tenenbaum, Jonathan Ragan-Kelley

Top. Cogn. Sci., 2023

Importance Sampling BRDF Derivatives.

Yash Belhe, Bing Xu, Sai Praveen Bangaru, Ravi Ramamoorthi, Tzu-Mao Li

CoRR, 2023

Parameter-space ReSTIR for Differentiable and Inverse Rendering.

Wesley Chang, Venkataram Sivaram, Derek Nowrouzezahrai, Toshiya Hachisuka, Ravi Ramamoorthi, Tzu-Mao Li

Proceedings of the ACM SIGGRAPH 2023 Conference Proceedings, 2023

Acting as Inverse Inverse Planning.

Kartik Chandra, Tzu-Mao Li, Joshua B. Tenenbaum, Jonathan Ragan-Kelley

Proceedings of the ACM SIGGRAPH 2023 Conference Proceedings, 2023

Inferring the Future by Imagining the Past.

Kartik Chandra, Tony Chen, Tzu-Mao Li, Jonathan Ragan-Kelley, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Factorized Inverse Path Tracing for Efficient and Accurate Material-Lighting Estimation.

Liwen Wu, Rui Zhu, Mustafa B. Yaldiz, Yinhao Zhu, Hong Cai, Janarbek Matai, Fatih Porikli, Tzu-Mao Li, Manmohan Chandraker, Ravi Ramamoorthi

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Storytelling as Inverse Inverse Planning.

Kartik Chandra, Tzu-Mao Li, Josh Tenenbaum, Jonathan Ragan-Kelley

Proceedings of the 45th Annual Meeting of the Cognitive Science Society, 2023

2022

Searching for Fast Demosaicking Algorithms.

Karima Ma, Michaël Gharbi, Andrew Adams, Shoaib Kamil, Tzu-Mao Li, Connelly Barnes, Jonathan Ragan-Kelley

ACM Trans. Graph., 2022

Differentiable Visual Computing: Challenges and Opportunities.

Tzu-Mao Li

IEEE Computer Graphics and Applications, 2022

Differentiable Rendering of Neural SDFs through Reparameterization.

Sai Praveen Bangaru, Michaël Gharbi, Fujun Luan, Tzu-Mao Li, Kalyan Sunkavalli, Milos Hasan, Sai Bi, Zexiang Xu, Gilbert Bernstein, Frédo Durand

Proceedings of the SIGGRAPH Asia 2022 Conference Papers, 2022

Designing Perceptual Puzzles by Differentiating Probabilistic Programs.

Kartik Chandra, Tzu-Mao Li, Joshua B. Tenenbaum, Jonathan Ragan-Kelley

Proceedings of the SIGGRAPH '22: Special Interest Group on Computer Graphics and Interactive Techniques Conference, Vancouver, BC, Canada, August 7, 2022

2021

Learning to cluster for rendering with many lights.

Yu-Chen Wang, Yu-Ting Wu, Tzu-Mao Li, Yung-Yu Chuang

ACM Trans. Graph., 2021

Systematically differentiating parametric discontinuities.

Sai Praveen Bangaru, Jesse Michel, Kevin Mu, Gilbert Bernstein, Tzu-Mao Li, Jonathan Ragan-Kelley

ACM Trans. Graph., 2021

Efficient automatic scheduling of imaging and vision pipelines for the GPU.

Luke Anderson, Andrew Adams, Karima Ma, Tzu-Mao Li, Tian Jin, Jonathan Ragan-Kelley

Proc. ACM Program. Lang., 2021

Small in-distribution changes in 3D perspective and lighting fool both CNNs and Transformers.

Spandan Madan, Tomotake Sasaki, Tzu-Mao Li, Xavier Boix, Hanspeter Pfister

CoRR, 2021

Distributed and Heterogeneous SAR Backprojection with Halide.

Connor Imes, Tzu-Mao Li, Mark Glines, Rishi Khan, John Paul Walters

Proceedings of the 2021 IEEE High Performance Extreme Computing Conference, 2021

2020

Differentiable vector graphics rasterization for editing and learning.

Tzu-Mao Li, Michal Lukác, Michaël Gharbi, Jonathan Ragan-Kelley

ACM Trans. Graph., 2020

Unbiased warped-area sampling for differentiable rendering.

Sai Praveen Bangaru, Tzu-Mao Li, Frédo Durand

ACM Trans. Graph., 2020

Learning to Schedule Halide Pipelines for the GPU.

Luke Anderson, Andrew Adams, Karima Ma, Tzu-Mao Li, Jonathan Ragan-Kelley

CoRR, 2020

Differentiating a Tensor Language.

Gilbert Bernstein, Michael Mara, Tzu-Mao Li, Dougal Maclaurin, Jonathan Ragan-Kelley

CoRR, 2020

Physics-based differentiable rendering: from theory to implementation.

Shuang Zhao, Wenzel Jakob, Tzu-Mao Li

Proceedings of the SIGGRAPH 2020: Special Interest Group on Computer Graphics and Interactive Techniques Conference, 2020

DiffTaichi: Differentiable Programming for Physical Simulation.

Yuanming Hu, Luke Anderson, Tzu-Mao Li, Qi Sun, Nathan Carr, Jonathan Ragan-Kelley, Frédo Durand

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Taichi: a language for high-performance computation on spatially sparse data structures.

Yuanming Hu, Tzu-Mao Li, Luke Anderson, Jonathan Ragan-Kelley, Frédo Durand

ACM Trans. Graph., 2019

Sample-based Monte Carlo denoising using a kernel-splatting network.

Michaël Gharbi, Tzu-Mao Li, Miika Aittala, Jaakko Lehtinen, Frédo Durand

ACM Trans. Graph., 2019

Learning to optimize halide with tree search and random programs.

Andrew Adams, Karima Ma, Luke Anderson, Riyadh Baghdadi, Tzu-Mao Li, Michaël Gharbi, Benoit Steiner, Steven Johnson, Kayvon Fatahalian, Frédo Durand, Jonathan Ragan-Kelley

ACM Trans. Graph., 2019

Differentiable Visual Computing.

Tzu-Mao Li

CoRR, 2019

Inverse Path Tracing for Joint Material and Lighting Estimation.

Dejan Azinovic, Tzu-Mao Li, Anton Kaplanyan, Matthias Nießner

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Differentiable programming for image processing and deep learning in halide.

Tzu-Mao Li, Michaël Gharbi, Andrew Adams, Frédo Durand, Jonathan Ragan-Kelley

ACM Trans. Graph., 2018

Differentiable Monte Carlo ray tracing through edge sampling.

Tzu-Mao Li, Miika Aittala, Frédo Durand, Jaakko Lehtinen

ACM Trans. Graph., 2018

2017

Aether: an embedded domain specific sampling language for Monte Carlo rendering.

Luke Anderson, Tzu-Mao Li, Jaakko Lehtinen, Frédo Durand

ACM Trans. Graph., 2017

2015

Dual-Matrix Sampling for Scalable Translucent Material Rendering.

Yu-Ting Wu, Tzu-Mao Li, Yu-Hsun Lin, Yung-Yu Chuang

IEEE Trans. Vis. Comput. Graph., 2015

Anisotropic Gaussian mutations for metropolis light transport through Hessian-Hamiltonian dynamics.

Tzu-Mao Li, Jaakko Lehtinen, Ravi Ramamoorthi, Wenzel Jakob, Frédo Durand

ACM Trans. Graph., 2015

2012

SURE-based optimization for adaptive sampling and reconstruction.

Tzu-Mao Li, Yu-Ting Wu, Yung-Yu Chuang

ACM Trans. Graph., 2012