Neural Importance Sampling

11 August 2018

Markus Gross

Papers citing "Neural Importance Sampling"

30 / 80 papers shown

Title
Neural BRDFs: Representation and Operations Jiahui Fan Beibei Wang Miloš Hašan Jian Yang Ling-Qi Yan AI4CE 32 6 0 06 Nov 2021
Generative Networks for Precision Enthusiasts A. Butter Theo Heimel Sander Hummerich Tobias Krebs Tilman Plehn Armand Rousselot Sophia Vent AI4CE 21 59 0 22 Oct 2021
Dynamic Diffuse Global Illumination Resampling Z. Majercik Thomas Müller A. Keller Derek Nowrouzezahrai M. McGuire 44 13 0 11 Aug 2021
Sparse Flows: Pruning Continuous-depth Models Lucas Liebenwein Ramin Hasani Alexander Amini Daniela Rus 26 16 0 24 Jun 2021
Real-time Neural Radiance Caching for Path Tracing Thomas Müller Fabrice Rousselle Jan Novák A. Keller 3DH AI4CE 36 155 0 23 Jun 2021
Nested Variational Inference Heiko Zimmermann Hao Wu Babak Esmaeili Jan-Willem van de Meent BDL 32 20 0 21 Jun 2021
Neural Radiosity Saeed Hadadan Shuhong Chen Matthias Zwicker 22 41 0 26 May 2021
Unbiased Monte Carlo Cluster Updates with Autoregressive Neural Networks Dian Wu R. Rossi Giuseppe Carleo 32 29 0 12 May 2021
Understanding Event-Generation Networks via Uncertainties Marco Bellagente Manuel Haussmann Michel Luchmann Tilman Plehn BDL 41 55 0 09 Apr 2021
Appearance-Driven Automatic 3D Model Simplification J. Hasselgren Jacob Munkberg J. Lehtinen M. Aittala S. Laine 48 55 0 08 Apr 2021
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform Achille Thin Yazid Janati Sylvain Le Corff Charles Ollion Arnaud Doucet Alain Durmus Eric Moulines C. Robert 35 7 0 17 Mar 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 48 485 0 08 Mar 2021
Jacobian Determinant of Normalizing Flows Huadong Liao Jiawei He DRL 19 7 0 12 Feb 2021
Variational Determinant Estimation with Spherical Normalizing Flows Simon Passenheim Emiel Hoogeboom BDL 31 1 0 24 Dec 2020
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang Ricky T. Q. Chen Christos Tsirigotis Aaron Courville OT 119 96 0 10 Dec 2020
Invertible Neural BRDF for Object Inverse Rendering Zhe Chen S. Nobuhara Ko Nishino BDL AI4CE 40 26 0 10 Aug 2020
Longitudinal Variational Autoencoder S. Ramchandran Gleb Tikhonov Kalle Kujanpää Miika Koskinen Harri Lähdesmäki DRL CML BDL 14 36 0 17 Jun 2020
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space Nikolas Nusken Lorenz Richter AI4CE 38 105 0 11 May 2020
VegasFlow: accelerating Monte Carlo simulation across multiple hardware platforms Stefano Carrazza J. Cruz-Martinez 9 25 0 28 Feb 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 57 176 0 16 Feb 2020
Targeted free energy estimation via learned mappings Peter Wirnsberger A. J. Ballard George Papamakarios Stuart Abercrombie S. Racanière Alexander Pritzel Danilo Jimenez Rezende Charles Blundell 27 86 0 12 Feb 2020
Normalizing Flows on Tori and Spheres Danilo Jimenez Rezende George Papamakarios S. Racanière M. S. Albergo G. Kanwar P. Shanahan Kyle Cranmer TPM 20 153 0 06 Feb 2020
i-flow: High-dimensional Integration and Sampling with Normalizing Flows Christina Gao J. Isaacson Claudius Krause AI4CE 24 107 0 15 Jan 2020
Invertible Generative Modeling using Linear Rational Splines H. M. Dolatabadi S. Erfani C. Leckie 34 65 0 15 Jan 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 67 1,635 0 05 Dec 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 27 8 0 10 Jun 2019
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 41 748 0 10 Jun 2019
Cubic-Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios TPM 53 57 0 05 Jun 2019
A RAD approach to deep mixture models Laurent Dinh Jascha Narain Sohl-Dickstein Hugo Larochelle Razvan Pascanu 22 45 0 18 Mar 2019
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 275 2,553 0 25 Jan 2016