{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T08:18:37Z","timestamp":1774685917921,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":58,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,7]],"date-time":"2022-08-07T00:00:00Z","timestamp":1659830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000006","name":"Office of Naval Research","doi-asserted-by":"publisher","award":["00010803"],"award-info":[{"award-number":["00010803"]}],"id":[{"id":"10.13039\/100000006","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005883","name":"Hertz Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005883","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006063","name":"Paul and Daisy Soros Fellowships for New Americans","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006063","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF (National Science Foundation)","doi-asserted-by":"publisher","award":["2105806, CCF-1231216, CCF-1723445, CCF-1846502, 1745302"],"award-info":[{"award-number":["2105806, CCF-1231216, CCF-1723445, CCF-1846502, 1745302"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,8,7]]},"DOI":"10.1145\/3528233.3530715","type":"proceedings-article","created":{"date-parts":[[2022,7,20]],"date-time":"2022-07-20T13:56:43Z","timestamp":1658325403000},"page":"1-9","source":"Crossref","is-referenced-by-count":13,"title":["Designing Perceptual Puzzles by Differentiating Probabilistic Programs"],"prefix":"10.1145","author":[{"given":"Kartik","family":"Chandra","sequence":"first","affiliation":[{"name":"Computer Science &amp; Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), United States of America"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tzu-Mao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering (CSE), University of California, San Diego, United States of America"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joshua","family":"Tenenbaum","sequence":"additional","affiliation":[{"name":"Department of Brain and Cognitive Sciences (BCS); Center for Brains, Minds &amp; Machines (CBMM); Computer Science &amp; Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), United States of America"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Ragan-Kelley","sequence":"additional","affiliation":[{"name":"Computer Science &amp; Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), United States of America"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,8,7]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cognition.2009.07.005"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450626.3459775"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1306572110"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Adrien Bousseau Emmanuelle Chapoulie Ravi Ramamoorthi and Maneesh Agrawala. 2011. Optimizing environment maps for material depiction. In Computer graphics forum Vol.\u00a030. 1171\u20131180. https:\/\/dl.acm.org\/doi\/abs\/10.1111\/j.1467-8659.2011.01975.x Adrien Bousseau Emmanuelle Chapoulie Ravi Ramamoorthi and Maneesh Agrawala. 2011. Optimizing environment maps for material depiction. In Computer graphics forum Vol.\u00a030. 1171\u20131180. https:\/\/dl.acm.org\/doi\/abs\/10.1111\/j.1467-8659.2011.01975.x","DOI":"10.1111\/j.1467-8659.2011.01975.x"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAA.14.001393"},{"key":"e_1_3_2_1_6_1","volume-title":"International Conference on Machine Learning. PMLR, 1238\u20131248","author":"Campbell Andrew","year":"2021","unstructured":"Andrew Campbell , Wenlong Chen , Vincent Stimper , Jose\u00a0Miguel Hernandez-Lobato , and Yichuan Zhang . 2021 . A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization . In International Conference on Machine Learning. PMLR, 1238\u20131248 . http:\/\/proceedings.mlr.press\/v139\/campbell21a\/campbell21a.pdf Andrew Campbell, Wenlong Chen, Vincent Stimper, Jose\u00a0Miguel Hernandez-Lobato, and Yichuan Zhang. 2021. A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization. In International Conference on Machine Learning. PMLR, 1238\u20131248. http:\/\/proceedings.mlr.press\/v139\/campbell21a\/campbell21a.pdf"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v076.i01"},{"key":"e_1_3_2_1_8_1","volume-title":"Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)","author":"Chandra Kartik","year":"1865","unstructured":"Kartik Chandra , Chuma Kabaghe , and Gregory Valiant . 2021. Beyond Laurel\/ Yanny : An Autoencoder-Enabled Search for Polyperceivable Audio . In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers) . Association for Computational Linguistics , Online , 593\u2013598. https:\/\/doi.org\/10. 1865 3\/v1\/2021.acl-short.75 Kartik Chandra, Chuma Kabaghe, and Gregory Valiant. 2021. Beyond Laurel\/Yanny: An Autoencoder-Enabled Search for Polyperceivable Audio. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers). Association for Computational Linguistics, Online, 593\u2013598. https:\/\/doi.org\/10.18653\/v1\/2021.acl-short.75"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/1360612.1360661"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1778765.1778788"},{"key":"e_1_3_2_1_11_1","volume-title":"Advances in Neural Information Processing Systems, H.\u00a0Wallach, H.\u00a0Larochelle, A.\u00a0Beygelzimer, F.\u00a0d'Alch\u00e9-Buc, E.\u00a0Fox, and R.\u00a0Garnett (Eds.). Vol.\u00a032. Curran Associates","author":"Dai Bo","year":"2019","unstructured":"Bo Dai , Zhen Liu , Hanjun Dai , Niao He , Arthur Gretton , Le Song , and Dale Schuurmans . 2019. Exponential Family Estimation via Adversarial Dynamics Embedding . In Advances in Neural Information Processing Systems, H.\u00a0Wallach, H.\u00a0Larochelle, A.\u00a0Beygelzimer, F.\u00a0d'Alch\u00e9-Buc, E.\u00a0Fox, and R.\u00a0Garnett (Eds.). Vol.\u00a032. Curran Associates , Inc .https:\/\/proceedings.neurips.cc\/paper\/ 2019 \/file\/767d01b4bac1a1e8824c9b9f7cc79a04-Paper.pdf Bo Dai, Zhen Liu, Hanjun Dai, Niao He, Arthur Gretton, Le Song, and Dale Schuurmans. 2019. Exponential Family Estimation via Adversarial Dynamics Embedding. In Advances in Neural Information Processing Systems, H.\u00a0Wallach, H.\u00a0Larochelle, A.\u00a0Beygelzimer, F.\u00a0d'Alch\u00e9-Buc, E.\u00a0Fox, and R.\u00a0Garnett (Eds.). Vol.\u00a032. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper\/2019\/file\/767d01b4bac1a1e8824c9b9f7cc79a04-Paper.pdf"},{"key":"e_1_3_2_1_12_1","volume-title":"Proceedings of the 38th International Conference on Machine Learning (ICML-21)","author":"Du Yilun","year":"2021","unstructured":"Yilun Du , Shuang Li , B.\u00a0 Joshua Tenenbaum , and Igor Mordatch . 2021 . Improved Contrastive Divergence Training of Energy Based Models . In Proceedings of the 38th International Conference on Machine Learning (ICML-21) . https:\/\/arxiv.org\/abs\/2012.01316 Yilun Du, Shuang Li, B.\u00a0Joshua Tenenbaum, and Igor Mordatch. 2021. Improved Contrastive Divergence Training of Energy Based Models. In Proceedings of the 38th International Conference on Machine Learning (ICML-21). https:\/\/arxiv.org\/abs\/2012.01316"},{"key":"e_1_3_2_1_13_1","volume-title":"Hybrid Monte Carlo. Physics letters B 195, 2","author":"Duane Simon","year":"1987","unstructured":"Simon Duane , Anthony\u00a0 D Kennedy , Brian\u00a0 J Pendleton , and Duncan Roweth . 1987. Hybrid Monte Carlo. Physics letters B 195, 2 ( 1987 ), 216\u2013222. https:\/\/archive.org\/download\/wikipedia-scholarly-sources-corpus\/10.1016%252F0361-9230%252887%252990129-8.zip\/10.1016%252F0370-2693%252887%252991197-X.pdf Simon Duane, Anthony\u00a0D Kennedy, Brian\u00a0J Pendleton, and Duncan Roweth. 1987. Hybrid Monte Carlo. Physics letters B 195, 2 (1987), 216\u2013222. https:\/\/archive.org\/download\/wikipedia-scholarly-sources-corpus\/10.1016%252F0361-9230%252887%252990129-8.zip\/10.1016%252F0370-2693%252887%252991197-X.pdf"},{"key":"e_1_3_2_1_14_1","volume-title":"SIGGRAPH 2002 Course# 13 Notes(2002)","author":"Durand Fr\u00e9do","year":"2002","unstructured":"Fr\u00e9do Durand , Maneesh Agrawala , Bruce Gooch , Victoria Interrante , Victor Ostromoukhov , and Denis Zorin . 2002 . Perceptual and artistic principles for effective computer depiction . SIGGRAPH 2002 Course# 13 Notes(2002) . http:\/\/people.csail.mit.edu\/fredo\/SIG02_ArtScience\/DepictionNotes2.pdf Fr\u00e9do Durand, Maneesh Agrawala, Bruce Gooch, Victoria Interrante, Victor Ostromoukhov, and Denis Zorin. 2002. Perceptual and artistic principles for effective computer depiction. SIGGRAPH 2002 Course# 13 Notes(2002). http:\/\/people.csail.mit.edu\/fredo\/SIG02_ArtScience\/DepictionNotes2.pdf"},{"key":"e_1_3_2_1_15_1","volume-title":"Adversarial examples that fool both computer vision and time-limited humans. Advances in neural information processing systems 31","author":"Elsayed Gamaleldin","year":"2018","unstructured":"Gamaleldin Elsayed , Shreya Shankar , Brian Cheung , Nicolas Papernot , Alexey Kurakin , Ian Goodfellow , and Jascha Sohl-Dickstein . 2018. Adversarial examples that fool both computer vision and time-limited humans. Advances in neural information processing systems 31 ( 2018 ). https:\/\/proceedings.neurips.cc\/paper\/2018\/file\/8562ae5e286544710b2e7ebe9858833b-Paper.pdf Gamaleldin Elsayed, Shreya Shankar, Brian Cheung, Nicolas Papernot, Alexey Kurakin, Ian Goodfellow, and Jascha Sohl-Dickstein. 2018. Adversarial examples that fool both computer vision and time-limited humans. Advances in neural information processing systems 31 (2018). https:\/\/proceedings.neurips.cc\/paper\/2018\/file\/8562ae5e286544710b2e7ebe9858833b-Paper.pdf"},{"key":"e_1_3_2_1_16_1","volume-title":"perception and Bayes. Nature neuroscience 5, 6","author":"Geisler S","year":"2002","unstructured":"Wilson\u00a0 S Geisler and Daniel Kersten . 2002. Illusions , perception and Bayes. Nature neuroscience 5, 6 ( 2002 ), 508\u2013510. https:\/\/www.cs.utexas.edu\/~dana\/NVGeisler2.pdf Wilson\u00a0S Geisler and Daniel Kersten. 2002. Illusions, perception and Bayes. Nature neuroscience 5, 6 (2002), 508\u2013510. https:\/\/www.cs.utexas.edu\/~dana\/NVGeisler2.pdf"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00021"},{"key":"e_1_3_2_1_18_1","unstructured":"Noah\u00a0D Goodman Joshua\u00a0B. Tenenbaum and The\u00a0ProbMods Contributors. 2016. Probabilistic Models of Cognition. http:\/\/probmods.org\/v2. Accessed: 2021-10-15. Noah\u00a0D Goodman Joshua\u00a0B. Tenenbaum and The\u00a0ProbMods Contributors. 2016. Probabilistic Models of Cognition. http:\/\/probmods.org\/v2. Accessed: 2021-10-15."},{"key":"e_1_3_2_1_19_1","volume-title":"Josh Tenenbaum, Dan Gutfreund, and Vikash Mansinghka.","author":"Gothoskar Nishad","year":"2021","unstructured":"Nishad Gothoskar , Marco Cusumano-Towner , Ben Zinberg , Matin Ghavamizadeh , Falk Pollok , Austin Garrett , Josh Tenenbaum, Dan Gutfreund, and Vikash Mansinghka. 2021 . 3DP3: 3D Scene Perception via Probabilistic Programming. Advances in Neural Information Processing Systems 34 (2021). https:\/\/proceedings.neurips.cc\/paper\/2021\/file\/4fc66104f8ada6257fa55f29a2a567c7-Paper.pdf Nishad Gothoskar, Marco Cusumano-Towner, Ben Zinberg, Matin Ghavamizadeh, Falk Pollok, Austin Garrett, Josh Tenenbaum, Dan Gutfreund, and Vikash Mansinghka. 2021. 3DP3: 3D Scene Perception via Probabilistic Programming. Advances in Neural Information Processing Systems 34 (2021). https:\/\/proceedings.neurips.cc\/paper\/2021\/file\/4fc66104f8ada6257fa55f29a2a567c7-Paper.pdf"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1177\/0301006620908207"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"Inbar Huberman and Raanan Fattal. 2015. Reducing Lateral Visual Biases in Displays. Computer Graphics Forum (CGF). https:\/\/www.cs.huji.ac.il\/w~raananf\/projects\/lateral_biases\/ Inbar Huberman and Raanan Fattal. 2015. Reducing Lateral Visual Biases in Displays. Computer Graphics Forum (CGF). https:\/\/www.cs.huji.ac.il\/w~raananf\/projects\/lateral_biases\/","DOI":"10.1111\/cgf.12739"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev.psych.55.090902.142005"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/1141911.1141937"},{"key":"e_1_3_2_1_24_1","unstructured":"Diederik\u00a0P Kingma and Max Welling. 2014. Auto-Encoding Variational Bayes. arxiv:1312.6114\u00a0[stat.ML] https:\/\/arxiv.org\/pdf\/1312.6114.pdf Diederik\u00a0P Kingma and Max Welling. 2014. Auto-Encoding Variational Bayes. arxiv:1312.6114\u00a0[stat.ML] https:\/\/arxiv.org\/pdf\/1312.6114.pdf"},{"key":"e_1_3_2_1_25_1","volume-title":"Perception as Bayesian inference","author":"Knill C","unstructured":"David\u00a0 C Knill and Whitman Richards . 1996. Perception as Bayesian inference . Cambridge University Press . David\u00a0C Knill and Whitman Richards. 1996. Perception as Bayesian inference. Cambridge University Press."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299068"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cub.2015.04.053"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00780"},{"key":"e_1_3_2_1_29_1","volume-title":"Is it warm? Is it real? Or just low spatial frequency?Science 290, 5495","author":"Livingstone S","year":"2000","unstructured":"Margaret\u00a0 S Livingstone . 2000. Is it warm? Is it real? Or just low spatial frequency?Science 290, 5495 ( 2000 ), 1299\u20131299. https:\/\/livingstone.hms.harvard.edu\/sites\/livingstone.hms.harvard.edu\/files\/publications\/2000_November17.%20Livingstone.%20Is%20It%20Warm_%20Is%20it%20Real_%20Or%20Just%20Low%20Spatial%20Frequency_.pdf Margaret\u00a0S Livingstone. 2000. Is it warm? Is it real? Or just low spatial frequency?Science 290, 5495 (2000), 1299\u20131299. https:\/\/livingstone.hms.harvard.edu\/sites\/livingstone.hms.harvard.edu\/files\/publications\/2000_November17.%20Livingstone.%20Is%20It%20Warm_%20Is%20it%20Real_%20Or%20Just%20Low%20Spatial%20Frequency_.pdf"},{"key":"e_1_3_2_1_30_1","volume-title":"Change blindness images","author":"Ma Li-Qian","year":"2013","unstructured":"Li-Qian Ma , Kun Xu , Tien-Tsin Wong , Bi-Ye Jiang , and Shi-Min Hu. 2013. Change blindness images . IEEE transactions on visualization and computer graphics 19, 11( 2013 ), 1808\u20131819. https:\/\/cg.cs.tsinghua.edu.cn\/papers\/TVCG-2013-changeblindness.pdf Li-Qian Ma, Kun Xu, Tien-Tsin Wong, Bi-Ye Jiang, and Shi-Min Hu. 2013. Change blindness images. IEEE transactions on visualization and computer graphics 19, 11(2013), 1808\u20131819. https:\/\/cg.cs.tsinghua.edu.cn\/papers\/TVCG-2013-changeblindness.pdf"},{"key":"e_1_3_2_1_31_1","volume-title":"International conference on machine learning. PMLR, 2113\u20132122","author":"Maclaurin Dougal","year":"2015","unstructured":"Dougal Maclaurin , David Duvenaud , and Ryan Adams . 2015 . Gradient-based hyperparameter optimization through reversible learning . In International conference on machine learning. PMLR, 2113\u20132122 . http:\/\/proceedings.mlr.press\/v37\/maclaurin15.pdf Dougal Maclaurin, David Duvenaud, and Ryan Adams. 2015. Gradient-based hyperparameter optimization through reversible learning. In International conference on machine learning. PMLR, 2113\u20132122. http:\/\/proceedings.mlr.press\/v37\/maclaurin15.pdf"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Pascal Mamassian Michael Landy and Laurence\u00a0T Maloney. 2002. Bayesian modelling of visual perception. Probabilistic models of the brain(2002) 13\u201336. http:\/\/mamassian.free.fr\/papers\/mamassian_mit02.pdf Pascal Mamassian Michael Landy and Laurence\u00a0T Maloney. 2002. Bayesian modelling of visual perception. Probabilistic models of the brain(2002) 13\u201336. http:\/\/mamassian.free.fr\/papers\/mamassian_mit02.pdf","DOI":"10.7551\/mitpress\/5583.003.0005"},{"key":"e_1_3_2_1_33_1","volume-title":"Advances in Neural Information Processing Systems, C.\u00a0J.\u00a0C. Burges, L.\u00a0Bottou, M.\u00a0Welling, Z.\u00a0Ghahramani, and K.\u00a0Q","author":"Mansinghka K","year":"2013","unstructured":"Vikash\u00a0 K Mansinghka , Tejas\u00a0 D Kulkarni , Yura\u00a0 N Perov , and Josh Tenenbaum . 2013. Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs . In Advances in Neural Information Processing Systems, C.\u00a0J.\u00a0C. Burges, L.\u00a0Bottou, M.\u00a0Welling, Z.\u00a0Ghahramani, and K.\u00a0Q . Weinberger (Eds.). Vol.\u00a026. Curran Associates, Inc .https:\/\/proceedings.neurips.cc\/paper\/ 2013 \/file\/fa14d4fe2f19414de3ebd9f63d5c0169-Paper.pdf Vikash\u00a0K Mansinghka, Tejas\u00a0D Kulkarni, Yura\u00a0N Perov, and Josh Tenenbaum. 2013. Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. In Advances in Neural Information Processing Systems, C.\u00a0J.\u00a0C. Burges, L.\u00a0Bottou, M.\u00a0Welling, Z.\u00a0Ghahramani, and K.\u00a0Q. Weinberger (Eds.). Vol.\u00a026. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper\/2013\/file\/fa14d4fe2f19414de3ebd9f63d5c0169-Paper.pdf"},{"key":"e_1_3_2_1_34_1","volume-title":"Vision","author":"Marr David","unstructured":"David Marr . 1982. Vision . W. H. Freeman and Company . https:\/\/mitpress.mit.edu\/books\/vision David Marr. 1982. Vision. W. H. Freeman and Company. https:\/\/mitpress.mit.edu\/books\/vision"},{"key":"e_1_3_2_1_35_1","first-page":"1","article-title":"Monte Carlo Gradient Estimation in Machine Learning.J","volume":"21","author":"Mohamed Shakir","year":"2020","unstructured":"Shakir Mohamed , Mihaela Rosca , Michael Figurnov , and Andriy Mnih . 2020 . Monte Carlo Gradient Estimation in Machine Learning.J . Mach. Learn. Res. 21 , 132 (2020), 1 \u2013 62 . https:\/\/arxiv.org\/pdf\/1906.10652.pdf Shakir Mohamed, Mihaela Rosca, Michael Figurnov, and Andriy Mnih. 2020. Monte Carlo Gradient Estimation in Machine Learning.J. Mach. Learn. Res. 21, 132 (2020), 1\u201362. https:\/\/arxiv.org\/pdf\/1906.10652.pdf","journal-title":"Mach. Learn. Res."},{"key":"e_1_3_2_1_36_1","volume-title":"Advances in Neural Information Processing Systems, C.\u00a0Cortes, N.\u00a0Lawrence, D.\u00a0Lee, M.\u00a0Sugiyama, and R.\u00a0Garnett (Eds.). Vol.\u00a028. Curran Associates","author":"Mohasel\u00a0Afshar Hadi","year":"2015","unstructured":"Hadi Mohasel\u00a0Afshar and Justin Domke . 2015. Reflection, Refraction, and Hamiltonian Monte Carlo . In Advances in Neural Information Processing Systems, C.\u00a0Cortes, N.\u00a0Lawrence, D.\u00a0Lee, M.\u00a0Sugiyama, and R.\u00a0Garnett (Eds.). Vol.\u00a028. Curran Associates , Inc .https:\/\/proceedings.neurips.cc\/paper\/ 2015 \/file\/8303a79b1e19a194f1875981be5bdb6f-Paper.pdf Hadi Mohasel\u00a0Afshar and Justin Domke. 2015. Reflection, Refraction, and Hamiltonian Monte Carlo. In Advances in Neural Information Processing Systems, C.\u00a0Cortes, N.\u00a0Lawrence, D.\u00a0Lee, M.\u00a0Sugiyama, and R.\u00a0Garnett (Eds.). Vol.\u00a028. Curran Associates, Inc.https:\/\/proceedings.neurips.cc\/paper\/2015\/file\/8303a79b1e19a194f1875981be5bdb6f-Paper.pdf"},{"key":"e_1_3_2_1_37_1","volume-title":"MCMC using Hamiltonian dynamics. Handbook of Markov chain Monte Carlo 2, 11","author":"M Neal","year":"2011","unstructured":"Radford\u00a0 M Neal 2011. MCMC using Hamiltonian dynamics. Handbook of Markov chain Monte Carlo 2, 11 ( 2011 ), 2. https:\/\/arxiv.org\/pdf\/1206.1901.pdf Radford\u00a0M Neal 2011. MCMC using Hamiltonian dynamics. Handbook of Markov chain Monte Carlo 2, 11 (2011), 2. https:\/\/arxiv.org\/pdf\/1206.1901.pdf"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1145\/1900354.1900400"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/1141911.1141919"},{"key":"e_1_3_2_1_40_1","volume-title":"3D Unsharp Masking for Scene Coherent Enhancement. Vol.\u00a027","author":"Ritschel Tobias","unstructured":"Tobias Ritschel , Kaleigh Smith , Matthias Ihrke , Thorsten Grosch , Karol Myszkowski , and Hans-Peter Seidel . 2008. 3D Unsharp Masking for Scene Coherent Enhancement. Vol.\u00a027 . Association for Computing Machinery , New York, NY, USA , 1\u20138. https:\/\/doi.org\/10.1145\/1360612.1360689 Tobias Ritschel, Kaleigh Smith, Matthias Ihrke, Thorsten Grosch, Karol Myszkowski, and Hans-Peter Seidel. 2008. 3D Unsharp Masking for Scene Coherent Enhancement. Vol.\u00a027. Association for Computing Machinery, New York, NY, USA, 1\u20138. https:\/\/doi.org\/10.1145\/1360612.1360689"},{"key":"e_1_3_2_1_41_1","volume-title":"International Conference on Machine Learning. PMLR, 1218\u20131226","author":"Salimans Tim","year":"2015","unstructured":"Tim Salimans , Diederik Kingma , and Max Welling . 2015 . Markov chain Monte Carlo and variational inference: Bridging the gap . In International Conference on Machine Learning. PMLR, 1218\u20131226 . http:\/\/proceedings.mlr.press\/v37\/salimans15.pdf Tim Salimans, Diederik Kingma, and Max Welling. 2015. Markov chain Monte Carlo and variational inference: Bridging the gap. In International Conference on Machine Learning. PMLR, 1218\u20131226. http:\/\/proceedings.mlr.press\/v37\/salimans15.pdf"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.3758\/BF03200759"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2019.08.034"},{"key":"e_1_3_2_1_44_1","volume-title":"International Conference on Learning Representations. http:\/\/arxiv.org\/abs\/1312","author":"Szegedy Christian","year":"2014","unstructured":"Christian Szegedy , Wojciech Zaremba , Ilya Sutskever , Joan Bruna , Dumitru Erhan , Ian Goodfellow , and Rob Fergus . 2014 . Intriguing properties of neural networks . In International Conference on Learning Representations. http:\/\/arxiv.org\/abs\/1312 .6199 Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2014. Intriguing properties of neural networks. In International Conference on Learning Representations. http:\/\/arxiv.org\/abs\/1312.6199"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/1274871.1274889"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1068\/p270671"},{"key":"e_1_3_2_1_47_1","volume-title":"International Conference on Machine Learning. PMLR, 9680\u20139689","author":"Vahdat Arash","year":"2020","unstructured":"Arash Vahdat , Evgeny Andriyash , and William Macready . 2020 . Undirected graphical models as approximate posteriors . In International Conference on Machine Learning. PMLR, 9680\u20139689 . http:\/\/proceedings.mlr.press\/v119\/vahdat20a\/vahdat20a.pdf Arash Vahdat, Evgeny Andriyash, and William Macready. 2020. Undirected graphical models as approximate posteriors. In International Conference on Machine Learning. PMLR, 9680\u20139689. http:\/\/proceedings.mlr.press\/v119\/vahdat20a\/vahdat20a.pdf"},{"key":"e_1_3_2_1_48_1","unstructured":"Jan-Willem van\u00a0de Meent Brooks Paige Hongseok Yang and Frank Wood. 2018. An introduction to probabilistic programming. arXiv preprint arXiv:1809.10756(2018). https:\/\/arxiv.org\/pdf\/1809.10756 Jan-Willem van\u00a0de Meent Brooks Paige Hongseok Yang and Frank Wood. 2018. An introduction to probabilistic programming. arXiv preprint arXiv:1809.10756(2018). https:\/\/arxiv.org\/pdf\/1809.10756"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1167\/17.4.5"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Pascal Wallisch and Michael Karlovich. 2019. Disagreeing about Crocs and socks: Creating profoundly ambiguous color displays. arXiv preprint arXiv:1908.05736(2019). https:\/\/arxiv.org\/pdf\/1908.05736.pdf Pascal Wallisch and Michael Karlovich. 2019. Disagreeing about Crocs and socks: Creating profoundly ambiguous color displays. arXiv preprint arXiv:1908.05736(2019). https:\/\/arxiv.org\/pdf\/1908.05736.pdf","DOI":"10.31234\/osf.io\/zpqnv"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450626.3459943"},{"key":"e_1_3_2_1_52_1","volume-title":"Motion illusions as optimal percepts. Nature neuroscience 5, 6","author":"Weiss Yair","year":"2002","unstructured":"Yair Weiss , Eero\u00a0 P Simoncelli , and Edward\u00a0 H Adelson . 2002. Motion illusions as optimal percepts. Nature neuroscience 5, 6 ( 2002 ), 598\u2013604. https:\/\/www.nature.com\/articles\/nn858 Yair Weiss, Eero\u00a0P Simoncelli, and Edward\u00a0H Adelson. 2002. Motion illusions as optimal percepts. Nature neuroscience 5, 6 (2002), 598\u2013604. https:\/\/www.nature.com\/articles\/nn858"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAA.381311"},{"key":"e_1_3_2_1_54_1","volume-title":"Proceedings of the 17th International conference on Artificial Intelligence and Statistics. 1024\u20131032","author":"Wood Frank","year":"2014","unstructured":"Frank Wood , Jan\u00a0Willem van\u00a0de Meent , and Vikash Mansinghka . 2014 . A New Approach to Probabilistic Programming Inference . In Proceedings of the 17th International conference on Artificial Intelligence and Statistics. 1024\u20131032 . https:\/\/probprog.github.io\/anglican\/assets\/pdf\/wood-aistats-2014.pdf Frank Wood, Jan\u00a0Willem van\u00a0de Meent, and Vikash Mansinghka. 2014. A New Approach to Probabilistic Programming Inference. In Proceedings of the 17th International conference on Artificial Intelligence and Statistics. 1024\u20131032. https:\/\/probprog.github.io\/anglican\/assets\/pdf\/wood-aistats-2014.pdf"},{"key":"e_1_3_2_1_55_1","volume-title":"Differentiable annealed importance sampling and the perils of gradient noise. Advances in Neural Information Processing Systems 34","author":"Zhang Guodong","year":"2021","unstructured":"Guodong Zhang , Kyle Hsu , Jianing Li , Chelsea Finn , and Roger\u00a0 B Grosse . 2021. Differentiable annealed importance sampling and the perils of gradient noise. Advances in Neural Information Processing Systems 34 ( 2021 ). https:\/\/proceedings.neurips.cc\/paper\/2021\/file\/a1a609f1ac109d0be28d8ae112db1bbb-Paper.pdf Guodong Zhang, Kyle Hsu, Jianing Li, Chelsea Finn, and Roger\u00a0B Grosse. 2021. Differentiable annealed importance sampling and the perils of gradient noise. Advances in Neural Information Processing Systems 34 (2021). https:\/\/proceedings.neurips.cc\/paper\/2021\/file\/a1a609f1ac109d0be28d8ae112db1bbb-Paper.pdf"},{"key":"e_1_3_2_1_56_1","volume-title":"Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research, Vol.\u00a089)","author":"Zhou Yuan","year":"2019","unstructured":"Yuan Zhou , Bradley\u00a0 J. Gram-Hansen , Tobias Kohn , Tom Rainforth , Hongseok Yang , and Frank Wood . 2019 . LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models . In Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research, Vol.\u00a089) , Kamalika Chaudhuri and Masashi Sugiyama (Eds.). PMLR, 148\u2013157. https:\/\/proceedings.mlr.press\/v89\/zhou19b.html Yuan Zhou, Bradley\u00a0J. Gram-Hansen, Tobias Kohn, Tom Rainforth, Hongseok Yang, and Frank Wood. 2019. LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models. In Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics(Proceedings of Machine Learning Research, Vol.\u00a089), Kamalika Chaudhuri and Masashi Sugiyama (Eds.). PMLR, 148\u2013157. https:\/\/proceedings.mlr.press\/v89\/zhou19b.html"},{"key":"e_1_3_2_1_57_1","volume-title":"Humans can decipher adversarial images. Nature communications 10, 1","author":"Zhou Zhenglong","year":"2019","unstructured":"Zhenglong Zhou and Chaz Firestone . 2019. Humans can decipher adversarial images. Nature communications 10, 1 ( 2019 ), 1\u20139. https:\/\/www.nature.com\/articles\/s41467-019-08931-6 Zhenglong Zhou and Chaz Firestone. 2019. Humans can decipher adversarial images. Nature communications 10, 1 (2019), 1\u20139. https:\/\/www.nature.com\/articles\/s41467-019-08931-6"},{"key":"e_1_3_2_1_58_1","volume-title":"Slice Sampling Reparameterization Gradients. In Third Symposium on Advances in Approximate Bayesian Inference. https:\/\/openreview.net\/pdf?id=cT_RMSqVf4","author":"Zoltowski M","year":"2020","unstructured":"David\u00a0 M Zoltowski , Diana Cai , and Ryan\u00a0 P Adams . 2020 . Slice Sampling Reparameterization Gradients. In Third Symposium on Advances in Approximate Bayesian Inference. https:\/\/openreview.net\/pdf?id=cT_RMSqVf4 David\u00a0M Zoltowski, Diana Cai, and Ryan\u00a0P Adams. 2020. Slice Sampling Reparameterization Gradients. In Third Symposium on Advances in Approximate Bayesian Inference. https:\/\/openreview.net\/pdf?id=cT_RMSqVf4"}],"event":{"name":"SIGGRAPH '22: Special Interest Group on Computer Graphics and Interactive Techniques Conference","location":"Vancouver BC Canada","acronym":"SIGGRAPH '22","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"]},"container-title":["Special Interest Group on Computer Graphics and Interactive Techniques Conference Proceedings"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3528233.3530715","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3528233.3530715","content-type":"text\/html","content-version":"vor","intended-application":"syndication"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:50Z","timestamp":1750186970000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3528233.3530715"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,7]]},"references-count":58,"alternative-id":["10.1145\/3528233.3530715","10.1145\/3528233"],"URL":"https:\/\/doi.org\/10.1145\/3528233.3530715","relation":{},"subject":[],"published":{"date-parts":[[2022,8,7]]}}}