SURE-based optimization for adaptive sampling and reconstruction. - Tzu-Mao Li; Yu-Ting Wu 001; Yung-Yu Chuang (ACM Trans. Graph., 2012)

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)

Dual-Matrix Sampling for Scalable Translucent Material Rendering. - Yu-Ting Wu 001; Tzu-Mao Li; Yu-Hsun Lin; Yung-Yu Chuang (IEEE Trans. Vis. Comput. Graph., 2015)

Aether: an embedded domain specific sampling language for Monte Carlo rendering. - Luke Anderson 001; Tzu-Mao Li; Jaakko Lehtinen; Frédo Durand (ACM Trans. Graph., 2017)

Differentiable Monte Carlo ray tracing through edge sampling. - Tzu-Mao Li; Miika Aittala; Frédo Durand; Jaakko Lehtinen (ACM Trans. Graph., 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)

Inverse Path Tracing for Joint Material and Lighting Estimation. - Dejan Azinovic; Tzu-Mao Li; Anton Kaplanyan; Matthias Nießner (CVPR, 2019)

Differentiable Visual Computing. - Tzu-Mao Li (CoRR, 2019)

Learning to optimize halide with tree search and random programs. - Andrew Adams; Karima Ma; Luke Anderson 001; Riyadh Baghdadi; Tzu-Mao Li; Michaël Gharbi; Benoit Steiner; Steven Johnson; Kayvon Fatahalian; Frédo Durand; Jonathan Ragan-Kelley (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)

Taichi: a language for high-performance computation on spatially sparse data structures. - Yuanming Hu; Tzu-Mao Li; Luke Anderson 001; Jonathan Ragan-Kelley; Frédo Durand (ACM Trans. Graph., 2019)

DiffTaichi: Differentiable Programming for Physical Simulation. - Yuanming Hu; Luke Anderson 001; Tzu-Mao Li; Qi Sun 003; Nathan Carr 001; Jonathan Ragan-Kelley; Frédo Durand (ICLR, 2020)

Physics-based differentiable rendering: from theory to implementation. - Shuang Zhao; Wenzel Jakob; Tzu-Mao Li (SIGGRAPH Courses, 2020)

Differentiating a Tensor Language. - Gilbert Bernstein; Michael Mara; Tzu-Mao Li; Dougal Maclaurin; Jonathan Ragan-Kelley (CoRR, 2020)

Learning to Schedule Halide Pipelines for the GPU. - Luke Anderson 001; Andrew Adams; Karima Ma; Tzu-Mao Li; Jonathan Ragan-Kelley (CoRR, 2020)

Unbiased warped-area sampling for differentiable rendering. - Sai Praveen Bangaru; Tzu-Mao Li; Frédo Durand (ACM Trans. Graph., 2020)

Differentiable vector graphics rasterization for editing and learning. - Tzu-Mao Li; Michal Lukác; Michaël Gharbi; Jonathan Ragan-Kelley (ACM Trans. Graph., 2020)

Multi-Resolution Shared Representative Filtering for Real-Time Depth Completion. - Yu-Ting Wu 001; Tzu-Mao Li; I-Chao Shen; Hong-Shiang Lin; Yung-Yu Chuang (High Performance Graphics (Symposium Papers), 2021)

Distributed and Heterogeneous SAR Backprojection with Halide. - Connor Imes; Tzu-Mao Li; Mark Glines; Rishi Khan; John Paul Walters (HPEC, 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)

Efficient automatic scheduling of imaging and vision pipelines for the GPU. - Luke Anderson 001; Andrew Adams; Karima Ma; Tzu-Mao Li; Tian Jin; Jonathan Ragan-Kelley (Proc. ACM Program. Lang., 2021)

Systematically differentiating parametric discontinuities. - Sai Praveen Bangaru; Jesse Michel; Kevin Mu; Gilbert Bernstein; Tzu-Mao Li; Jonathan Ragan-Kelley (ACM Trans. Graph., 2021)

Learning to cluster for rendering with many lights. - Yuchen Wang; Yu-Ting Wu 001; Tzu-Mao Li; Yung-Yu Chuang (ACM Trans. Graph., 2021)

Designing Perceptual Puzzles by Differentiating Probabilistic Programs. - Kartik Chandra; Tzu-Mao Li; Joshua B. Tenenbaum; Jonathan Ragan-Kelley (SIGGRAPH (Conference Paper Track), 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 (SIGGRAPH Asia, 2022)

Differentiable Visual Computing: Challenges and Opportunities. - Tzu-Mao Li (IEEE Computer Graphics and Applications, 2022)

Searching for Fast Demosaicking Algorithms. - Karima Ma; Michaël Gharbi; Andrew Adams; Shoaib Kamil 001; Tzu-Mao Li; Connelly Barnes; Jonathan Ragan-Kelley (ACM Trans. Graph., 2022)

Storytelling as Inverse Inverse Planning. - Kartik Chandra; Tzu-Mao Li; Josh Tenenbaum 001; Jonathan Ragan-Kelley (CogSci, 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 (ICCV, 2023)

Inferring the Future by Imagining the Past. - Kartik Chandra; Tony Chen 003; Tzu-Mao Li; Jonathan Ragan-Kelley; Josh Tenenbaum 001 (NeurIPS, 2023)

Acting as Inverse Inverse Planning. - Kartik Chandra; Tzu-Mao Li; Joshua B. Tenenbaum; Jonathan Ragan-Kelley (SIGGRAPH (Conference Paper Track), 2023)

Parameter-space ReSTIR for Differentiable and Inverse Rendering. - Wesley Chang; Venkataram Sivaram; Derek Nowrouzezahrai; Toshiya Hachisuka; Ravi Ramamoorthi; Tzu-Mao Li (SIGGRAPH (Conference Paper Track), 2023)

Storytelling as Inverse Inverse Planning. - Kartik Chandra; Tzu-Mao Li; Joshua B. Tenenbaum; Jonathan Ragan-Kelley (Top. Cogn. Sci., 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, 2023)

Physical Cyclic Animations. - Shiyang Jia; Stephanie Wang; Tzu-Mao Li; Albert Chern (Proc. ACM Comput. Graph. Interact. Tech., 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., 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., 2023)

Discontinuity-Aware 2D Neural Fields. - Yash Belhe; Michaël Gharbi; Matthew Fisher; Iliyan Georgiev; Ravi Ramamoorthi; Tzu-Mao Li (ACM Trans. Graph., 2023)

Warped-Area Reparameterization of Differential Path Integrals. - Peiyu Xu; Sai Praveen Bangaru; Tzu-Mao Li; Shuang Zhao (ACM Trans. Graph., 2023)

Enhancing Value Function Estimation through First-Order State-Action Dynamics in Offline Reinforcement Learning. - Yun-Hsuan Lien; Ping-Chun Hsieh; Tzu-Mao Li; Yu-Shuen Wang (ICML, 2024)

Neural Geometry Fields For Meshes. - Venkataram Edavamadathil Sivaram; Tzu-Mao Li; Ravi Ramamoorthi (SIGGRAPH (Conference Paper Track), 2024)

Spatiotemporal Bilateral Gradient Filtering for Inverse Rendering. - Wesley Chang; Xuanda Yang; Yash Belhe; Ravi Ramamoorthi; Tzu-Mao Li (SIGGRAPH Asia, 2024)

BSDF importance sampling using a diffusion model. - Ziyang Fu; Yash Belhe; Haolin Lu; Liwen Wu; Bing Xu; Tzu-Mao Li (SIGGRAPH Asia, 2024)

Markov-Chain Monte Carlo Sampling of Visibility Boundaries for Differentiable Rendering. - Peiyu Xu; Sai Praveen Bangaru; Tzu-Mao Li; Shuang Zhao (SIGGRAPH Asia, 2024)

WatChat: Explaining perplexing programs by debugging mental models. - Kartik Chandra; Tzu-Mao Li; Rachit Nigam; Joshua B. Tenenbaum; Jonathan Ragan-Kelley (CoRR, 2024)

HotSpot: Screened Poisson Equation for Signed Distance Function Optimization. - Zimo Wang; Cheng Wang; Taiki Yoshino; Sirui Tao; Ziyang Fu; Tzu-Mao Li (CoRR, 2024)

A Differentiable Wave Optics Model for End-to-End Computational Imaging System Optimization. - Chi-Jui Ho; Yash Belhe; Steve Rotenberg; Ravi Ramamoorthi; Tzu-Mao Li; Nicholas Antipa (CoRR, 2024)

Distributions for Compositionally Differentiating Parametric Discontinuities. - Jesse Michel; Kevin Mu; Xuanda Yang; Sai Praveen Bangaru; Elias Rojas Collins; Gilbert Bernstein; Jonathan Ragan-Kelley; Michael Carbin; Tzu-Mao Li (Proc. ACM Program. Lang., 2024)

Importance Sampling BRDF Derivatives. - Yash Belhe; Bing Xu; Sai Praveen Bangaru; Ravi Ramamoorthi; Tzu-Mao Li (ACM Trans. Graph., 2024)

Residual path integrals for re-rendering. - Bing Xu; Tzu-Mao Li; Iliyan Georgiev; Trevor Hedstrom; Ravi Ramamoorthi (Comput. Graph. Forum, 2024)

Temporally Stable Metropolis Light Transport Denoising using Recurrent Transformer Blocks. - Chuhao Chen 003; Yuze He; Tzu-Mao Li (ACM Trans. Graph., 2024)

Real-Time Path Guiding Using Bounding Voxel Sampling. - Haolin Lu; Wesley Chang; Trevor Hedstrom; Tzu-Mao Li (ACM Trans. Graph., 2024)

HotSpot: Signed Distance Function Optimization with an Asymptotically Sufficient Condition. - Zimo Wang; Cheng Wang; Taiki Yoshino; Sirui Tao; Ziyang Fu; Tzu-Mao Li (CVPR, 2025)

In-distribution adversarial attacks on object recognition models using gradient-free search. - Spandan Madan; Tomotake Sasaki; Hanspeter Pfister; Tzu-Mao Li; Xavier Boix (Trans. Mach. Learn. Res., 2025)

Transforming Unstructured Hair Strands into Procedural Hair Grooms. - Wesley Chang; Andrew L. Russell; Stephane Grabli; Matt Jen-Yuan Chiang; Christophe Hery; Doug Roble; Ravi Ramamoorthi; Tzu-Mao Li; Olivier Maury (ACM Trans. Graph., 2025)

Vector-Valued Monte Carlo Integration Using Ratio Control Variates. - Haolin Lu; Delio Vicini; Wesley Chang; Tzu-Mao Li (ACM Trans. Graph., 2025)