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Black swan: augmenting statistics with event data., , , , , , , , , and 4 other author(s). CIKM, page 2517-2520. ACM, (2011)Using chemical organization theory for model checking., , and . Bioinform., 25 (15): 1915-1922 (2009)Compressing molecular dynamics trajectories: Breaking the one-bit-per-sample barrier., , , and . J. Comput. Chem., 37 (20): 1897-1906 (2016)Towards rule-based metabolic databases: a requirement analysis based on KEGG., , , , and . IJDMB, 13 (3): 289-319 (2015)Zope 3 Developer's Handbook. SAMS, (2005)Compressing molecular dynamics trajectories: breaking the one-bit-per-sample barrier., , and . CoRR, (2016)Objects With Lighting: A Real-World Dataset for Evaluating Reconstruction and Rendering for Object Relighting., , , , , , , , and . CoRR, (2024)What Do Single-View 3D Reconstruction Networks Learn?, , , , , and . CVPR, page 3405-3414. Computer Vision Foundation / IEEE, (2019)Matryoshka Networks: Predicting 3D Geometry via Nested Shape Layers., and . CVPR, page 1936-1944. Computer Vision Foundation / IEEE Computer Society, (2018)A discriminative approach to perspective shape from shading in uncalibrated illumination., and . Comput. Graph., (2015)