[1] David J Anderson and Pietro Perona. Toward a science of computational ethology. Neuron, 84(1):18-31, 2014.
[2] Mackenzie Weygandt Mathis and Alexander Mathis. Deep learning tools for the measurement of animal behavior in neuroscience. Current opinion in neurobiology, 60:1-11, 2020.
[3] Mayank Kabra, Alice Robie, Marta Rivera-Alba, Steve Branson, and Kristin Branson. Jaaba: interactive machine learning for automatic annotation of animal behavior. Nature Methods, 10:64-67, 2013.
[4] Jennifer J Sun, Andrew Ulmer, Dipam Chakraborty, Brian Geuther, Edward Hayes, Heng Jia, Vivek Kumar, Zachary Partridge, Alice Robie, Catherine E Schretter, et al. The mabe22 benchmarks for representation learning of multi-agent behavior. arXiv preprint arXiv:2207.10553, 2022.
[5] Konrad Lorenz. The foundations of ethology. Springer verlag, 1981.
[6] Patrick C. Friman, Cooper, heron, and heward's applied behavior analysis (2nd ed.): Checkered flag for students and professors, yellow flag for the field. Journal of Applied Behavior Analysis, 43:161-174, 2010.
[7] Alexander Mathis, Pranav Mamidanna, Kevin M Cury, Taiga Abe, Venkatesh N Murthy, Mackenzie Weygandt Mathis, and Matthias Bethge. Deeplabcut: markerless pose estimation of user-defined body parts with deep learning. Nature neuroscience, 21(9):1281-1289, 2018.
[8] Fabrice de Chaumont, Elodie Ey, Nicolas Torquet, Thibault Lagache, Stephane Dallongeville, Albane Imbert, Thierry Legou, Anne-Marie Le Sourd, Philippe Faure, Thomas Bourgeron, and Jean-Christophe Olivo-Marin. Live mouse tracker: real-time behavioral analysis of groups of mice. bioRxiv, 2018.
[9] Talmo D Pereira, Diego E Aldarondo, Lindsay Willmore, Mikhail Kislin, Samuel S-H Wang, Mala Murthy, and Joshua W Shaevitz. Fast animal pose estimation using deep neural networks. Nature methods, 16(1):117-125, 2019.
[10] Kaiming He, Georgia Gkioxari, Piotr Dollár, and Ross Girshick. Mask r-cnn. In Proceedings of the IEEE international conference on computer vision, pages 2961-2969, 2017.
[11] Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C. Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick. Segment anything. arXiv:2304.02643, 2023.
[12] James P Bohnslav, Nivanthika K Wimalasena, Kelsey J Clausing, Yu Y Dai, David A Yarmolinsky, Tomás Cruz, Adam D Kashlan, M Eugenia Chiappe, Lauren L Orefice, Clifford J Woolf, et al. Deepethogram, a machine learning pipeline for supervised behavior classification from raw pixels. *Elite*, 10:e63377, 2021.
[13] Oliver Sturman, Lukas von Ziegler, Christa Schlappi, Furkan Akyol, Mattia Privitera, Daria Slominski, Christina Grimm, Laetitia Thieren, Valerio Zerbi, Benjamin Grewe, et al. Deep learning-based behavioral analysis reaches human accuracy and is capable of outperforming commercial solutions. Neuropsychopharmacology, 45(11):1942-1952, 2020.
[14] Simon RO Nilsson, Nastacia L Goodwin, Jia Jie Choong, Sophia Hwang, Hayden R Wright, Zane C Norville, Xiaoyu Tong, Dayu Lin, Brandon S Bentzley, Neir Eshel, et al. Simple behavioral analysis (simba)—an open source toolkit for computer classification of complex social behaviors in experimental animals. BioRxiv, pages 2020–04, 2020.
[15] Markus Marks, Qiuhan Jin, Oliver Sturman, Lukas M. von Ziegler, Sepp Kollmorgen, Wolfger von der Behrens, Valerio Mante, Johannes Bohacek, and Mehmet Fatih Yanik. Deep-learning based identification, tracking, pose estimation, and behavior classification of interacting primates and mice in complex environments. Nature machine intelligence, 4:331 - 340, 2020.