About
From the last 10 years or so, I have spent most of my time developing mathematical models to understand the role of randomness. I am fascinated by noise. Currently, I am investigating how noise plays a pivotal role in generative AI models. Before that, I spent a decade understanding how noise impacts the convergence behaviour of physically based light transport.
My name is Gurprit. I come from Jalandhar in Punjab, India. I did my schooling from Kendriya Vidyalaya No. 2, Jalandhar. I got into IIT Delhi and from there my journey started.
At the core of my research, I develop Monte Carlo sampling strategies for high-dimensional numerical integration problems. I am equally interested in applying Monte Carlo, Quasi-Monte Carlo and MCMC sampling strategies in generative modeling.
Publications
2025
Jump restore light transport
Sascha Holl, Gurprit Singh, Hans-Peter Seidel
SIGGRAPH Asia 2025
Gaussian integral linear operators for precomputed graphics
Haolin Lu, Yash Belhe, Gurprit Singh, Tzu-Mao Li, Toshiya Hachisuka
SIGGRAPH Asia 2025
Histogram Stratification for Spatio-Temporal Reservoir Sampling
Corentin Salaün, Martin Bálint, Laurent Belcour, Eric Heitz, Gurprit Singh, Karol Myszkowski
SIGGRAPH North America 2025
Demystifying noise: Role of randomness in generative AI
Gurprit Singh, Xingchang Huang, Jente Vandersanden, Cengiz Öztireli, Niloy Mitra
SIGGRAPH North America Courses 2025 / Eurographics Tutorial 2025
Edge-preserving noise for diffusion models
Jente Vandersanden, Sascha Holl, Xingchang Huang, Gurprit Singh
ICLR Workshop 2025
Q: What would be the impact of content-aware anisotropic noise on diffusion models?
Online importance sampling for stochastic gradient optimization
Corentin Salaun, Xingchang Huang, Iliyan Georgiev, Niloy Mitra, Gurprit Singh
ICPRAM 2025 — Best Student Paper Award
Q: Is there an efficient way to assign importance weights to mini-batch samples in gradient estimation?
Multiple importance sampling for stochastic gradient estimation
Corentin Salaun, Xingchang Huang, Iliyan Georgiev, Niloy Mitra, Gurprit Singh
ICPRAM 2025
Q: What if we have multiple importance strategies for gradient estimation?
2024
MCMC: Bridging Rendering, Optimization and Generative AI
Gurprit Singh, Wenzel Jakob
SIGGRAPH Asia Courses 2024
X: These notes are an effort to understand the role of MCMC sampling methods in rendering, optimization and generative AI.
Blue noise for diffusion models
Xingchang Huang, Corentin Salaun, Cristina Vasconcelos, Christian Theobalt, Cengiz Öztireli, Gurprit Singh
SIGGRAPH North America 2024
Q: How can we enhance generated samples simply from noise manipulation?
2023
Joint sampling and optimisation for inverse rendering
Martin Bálint, Karol Myszkowski, Hans-Peter Seidel, Gurprit Singh
SIGGRAPH Asia 2023
Q: How to reduce variance in gradient estimation during inverse rendering?
Perceptual error optimization for Monte Carlo animation rendering
Misa Korac, Corentin Salaun, Iliyan Georgiev, Pascal Grittmann, Philipp Slusallek, Karol Myszkowski, Gurprit Singh
SIGGRAPH Asia 2023 — conference track
Q: How to design perceptually motivated spatio-temporal masks for Monte Carlo animation rendering?
*Joint first authors.
Patternshop: Editing point patterns with image manipulations
Xingchang Huang, Tobias Ritschel, Hans-Peter Seidel, Pooran Memari, Gurprit Singh
SIGGRAPH North America 2023
Q: How can we design a 2D color-space that allows editing point patterns with Photoshop?
2022
Informatik Spektrum: Scalable multi-class sampling via filtered sliced optimal transport
Corentin Salaun, Iliyan Georgiev, Hans-Peter Seidel, Gurprit Singh
Cover image for Informatik Spektrum, October 2022
Scalable multi-class sampling via filtered sliced optimal transport
Corentin Salaun, Iliyan Georgiev, Hans-Peter Seidel, Gurprit Singh
SIGGRAPH Asia 2022 / ACM Transactions on Graphics, Volume 41, Issue 6, December 2022
Q: How can we build a unified framework for stippling, object placement and perceptually pleasing rendering?
Point-pattern synthesis using Gabor and random filters
Xingchang Huang, Pooran Memari, Hans-Peter Seidel, Gurprit Singh
EGSR 2022 / Computer Graphics Forum, Volume 41, Issue 6, July 2022
Q: How can we perform point pattern texture synthesis without training a network?
Regression-based Monte Carlo integration
Corentin Salaun, Adrien Gruson, Binh-Son Hua, Toshiya Hachisuka, Gurprit Singh
SIGGRAPH North America 2022 / ACM Transactions on Graphics, Volume 41, Issue 4, July 2022
Q: What happens if we use a polynomial function to average Monte Carlo estimates?
Perceptual error optimization for Monte Carlo rendering
Vassillen Chizhov, Iliyan Georgiev, Karol Myszkowski, Gurprit Singh
ACM Transactions on Graphics, Volume 41, Issue 3, June 2022 — presented at SIGGRAPH North America 2022
Q: How can we use a perception-based human visual system model to control the error distribution in rendering?
2021
Informatik Spektrum: Neural Light Field 3D Printing
Quan Zheng, Vahid Babaei, Gordon Wetzstein, Hans-Peter Seidel, Matthias Zwicker, Gurprit Singh
Cover image for Informatik Spektrum, October 2021
Neural Relightable Participating Media Rendering
Quan Zheng, Gurprit Singh, Hans-Peter Seidel
NeurIPS 2021
Blue Noise Plots
Christian van Onzenoodt, Gurprit Singh, Timo Ropinski, Tobias Ritschel
Eurographics 2021 / Computer Graphics Forum, Volume 40, Issue 2, May 2021
2020
Neural Light Field 3D Printing
Quan Zheng, Vahid Babaei, Gordon Wetzstein, Hans-Peter Seidel, Matthias Zwicker, Gurprit Singh
SIGGRAPH Asia 2020 / ACM Transactions on Graphics, Volume 39, Issue 6, December 2020
LadyBird: Quasi-Monte Carlo Sampling for Deep Implicit Field Based 3D Reconstruction with Symmetry
Yifan Xu, Tianqi Fan, Yi Yuan, Gurprit Singh
ECCV 2020 — Oral
*Contributed equally.
Real-time Monte Carlo Denoising with the Neural Bilateral Grid
Xiaoxu Meng, Quan Zheng, Amitabh Varshney, Gurprit Singh, Matthias Zwicker
Eurographics Symposium on Rendering 2020
2019
Deep Point Correlation Design
Thomas Leimkühler, Gurprit Singh, Karol Myszkowski, Hans-Peter Seidel, Tobias Ritschel
SIGGRAPH Asia 2019 / ACM Transactions on Graphics, Volume 38, Issue 6, October 2019
Analysis of Sample Correlations for Monte Carlo Rendering
Gurprit Singh, Cengiz Öztireli, Abdalla G. M. Ahmed, David Coeurjolly, Kartic Subr, Oliver Deussen, Victor Ostromoukhov, Ravi Ramamoorthi, Wojciech Jarosz
Computer Graphics Forum — Proceedings of Eurographics State of the Art Reports 2019
Fourier Analysis of Correlated Monte Carlo Importance Sampling
Gurprit Singh, Kartic Subr, David Coeurjolly, Victor Ostromoukhov, Wojciech Jarosz
Computer Graphics Forum, Volume 38, Issue 1, 2019
A Perception-driven Hybrid Decomposition for Multi-layer Accommodative Displays
Hyeonseung Yu, Mojtaba Bemana, Marek Wernikowski, Michał Chwesiuk, Okan Tarhan Tursun, Gurprit Singh, Karol Myszkowski, Radosław Mantiuk, Hans-Peter Seidel, Piotr Didyk
IEEE VR 2019
2018
Spectral Measures of Distortion for Change Detection in Dynamic Graphs
Luca Castelli Aleardi, Semih Salihoglu, Gurprit Singh, Maks Ovsjanikov
Complex Networks 2018 — Oral
Sampling Analysis using Correlations for Monte Carlo Rendering
Cengiz Öztireli, Gurprit Singh
SIGGRAPH Asia Courses 2018
End-to-end Sampling Patterns
Thomas Leimkühler, Gurprit Singh, Karol Myszkowski, Hans-Peter Seidel, Tobias Ritschel
Technical Report
2017
Convergence Analysis for Anisotropic Monte Carlo Sampling Spectra
Gurprit Singh, Wojciech Jarosz
SIGGRAPH 2017 / ACM Transactions on Graphics, Volume 36, Issue 4, July 2017
Variance and Convergence Analysis of Monte Carlo Line and Segment Samples
Gurprit Singh, Bailey Miller, Wojciech Jarosz
Computer Graphics Forum — Proceedings of EGSR, Volume 36, Issue 4, June 2017
2016
Monte Carlo Convergence Analysis for Anisotropic Sampling Power Spectra
Gurprit Singh, Wojciech Jarosz
Technical Report
Fourier Analysis of Numerical Integration in Monte Carlo Rendering: Theory and Practice
Kartic Subr, Gurprit Singh, Wojciech Jarosz
SIGGRAPH Courses 2016
project page / ACM / source code
2015
Variance and Sampling Analysis for Monte Carlo Integration in the Spherical Domain
Gurprit Singh
Ph.D. Dissertation, Université Lyon 1, France, September 2015
Variance Analysis for Monte Carlo Integration
Adrien Pilleboue, Gurprit Singh, David Coeurjolly, Michael Kazhdan, Victor Ostromoukhov
SIGGRAPH 2015 / ACM Transactions on Graphics, Volume 34, Issue 4, 2015
project page / ACM / source code
*Joint first authors.
Variance Analysis for Monte Carlo Integration: A Representation-Theoretic Perspective
Michael Kazhdan, Gurprit Singh, Adrien Pilleboue, David Coeurjolly, Victor Ostromoukhov
Technical Report
2014
Fast Tile-Based Adaptive Sampling with User-Specified Fourier Spectra
Florent Wachtel, Adrien Pilleboue, David Coeurjolly, Katherine Breeden, Gurprit Singh, Gaël Cathelin, Fernando de Goes, Mathieu Desbrun, Victor Ostromoukhov
SIGGRAPH 2014 / ACM Transactions on Graphics, Volume 33, Issue 4, 2014