| Example-based synthesis of 3D object arrangements M Fisher, D Ritchie, M Savva, T Funkhouser, P Hanrahan ACM Transactions on Graphics (TOG) 31 (6), 1-11, 2012 | 256 | 2012 |
| Interactive simulation of surgical needle insertion and steering N Chentanez, R Alterovitz, D Ritchie, L Cho, KK Hauser, K Goldberg, ... ACM SIGGRAPH 2009 papers, 1-10, 2009 | 182 | 2009 |
| Dynamic local remeshing for elastoplastic simulation M Wicke, D Ritchie, BM Klingner, S Burke, JR Shewchuk, JF O'Brien ACM Transactions on graphics (TOG) 29 (4), 1-11, 2010 | 180 | 2010 |
| Scancomplete: Large-scale scene completion and semantic segmentation for 3d scans A Dai, D Ritchie, M Bokeloh, S Reed, J Sturm, M Nießner Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 123 | 2018 |
| Learning to infer graphics programs from hand-drawn images K Ellis, D Ritchie, A Solar-Lezama, J Tenenbaum Advances in neural information processing systems, 6059-6068, 2018 | 114 | 2018 |
| Probabilistic color-by-numbers: Suggesting pattern colorizations using factor graphs S Lin, D Ritchie, M Fisher, P Hanrahan ACM Transactions on Graphics (TOG) 32 (4), 1-12, 2013 | 82 | 2013 |
| Deep convolutional priors for indoor scene synthesis K Wang, M Savva, AX Chang, D Ritchie ACM Transactions on Graphics (TOG) 37 (4), 1-14, 2018 | 78 | 2018 |
| Controlling procedural modeling programs with stochastically-ordered sequential monte carlo D Ritchie, B Mildenhall, ND Goodman, P Hanrahan ACM Transactions on Graphics (TOG) 34 (4), 1-11, 2015 | 65 | 2015 |
| Deep amortized inference for probabilistic programs D Ritchie, P Horsfall, ND Goodman arXiv preprint arXiv:1610.05735, 2016 | 62 | 2016 |
| d. tour: Style-based exploration of design example galleries D Ritchie, AA Kejriwal, SR Klemmer Proceedings of the 24th annual ACM symposium on User interface software and …, 2011 | 40 | 2011 |
| Planit: Planning and instantiating indoor scenes with relation graph and spatial prior networks K Wang, YA Lin, B Weissmann, M Savva, AX Chang, D Ritchie ACM Transactions on Graphics (TOG) 38 (4), 1-15, 2019 | 38 | 2019 |
| Improving shape deformation in unsupervised image-to-image translation A Gokaslan, V Ramanujan, D Ritchie, K In Kim, J Tompkin Proceedings of the European Conference on Computer Vision (ECCV), 649-665, 2018 | 35 | 2018 |
| Neurally-guided procedural models: Amortized inference for procedural graphics programs using neural networks D Ritchie, A Thomas, P Hanrahan, N Goodman Advances in neural information processing systems 29, 622-630, 2016 | 35 | 2016 |
| Fast and flexible indoor scene synthesis via deep convolutional generative models D Ritchie, K Wang, Y Lin Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 34 | 2019 |
| C3: Lightweight incrementalized MCMC for probabilistic programs using continuations and callsite caching D Ritchie, A Stuhlmüller, N Goodman Artificial Intelligence and Statistics, 28-37, 2016 | 24 | 2016 |
| Learning to describe scenes with programs Y Liu, Z Wu International Conference on Learning Representations, 2019 | 23 | 2019 |
| First-class runtime generation of high-performance types using exotypes Z DeVito, D Ritchie, M Fisher, A Aiken, P Hanrahan Proceedings of the 35th ACM SIGPLAN Conference on Programming Language …, 2014 | 18 | 2014 |
| Generating design suggestions under tight constraints with gradient‐based probabilistic programming D Ritchie, S Lin, ND Goodman, P Hanrahan Computer Graphics Forum 34 (2), 515-526, 2015 | 17 | 2015 |
| Learning generative models of 3D structures S Chaudhuri, D Ritchie, J Wu, K Xu, H Zhang Computer Graphics Forum 39 (2), 643-666, 2020 | 10 | 2020 |
| Neurally-guided procedural models: learning to guide procedural models with deep neural networks D Ritchie, A Thomas, P Hanrahan, ND Goodman arXiv preprint arXiv:1603.06143, 2016 | 10 | 2016 |
Patrick HanrahanStanford UniversityVerified email at cs.stanford.edu
