Published January 5, 2023
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Archetypes of the jumping spider (Araneae: Salticidae) as derived by intelligent machines
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Hill, David E. (2023): Archetypes of the jumping spider (Araneae: Salticidae) as derived by intelligent machines. Peckhamia 288 (1): 1-30, DOI: 10.5281/zenodo.7522509
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- Ai 2021. Shireen Ai. 13 JAN 2021. Dada and Surrealism, in brief. Online at https://www.researchgate.net/publication/ 348437078_ Dada_and_Surrealism_in_Brief
- Bang & Shim 2018. Duhyeon Bang and Hyunjung Shim. Improved training of Generative Adversarial Networks using representative features. Proceedings of the 35th International Conference on Machine Learning, Stockholm, Sweden PMLR 80, 2018.
- Bartos 2022. Maciej Bartos. Visual prey categorization by a generalist jumping spider. The European Zoological Journal 89 (1): 1312-1324.
- Chen et al. 2021. Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu and Wen Gao. 8 NOV 2021. Pre-trained image processing transformer. Cornell University arXiv:2012.00364v4.
- Choi et al. 2022. Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim and Sungroh Yoon. 1 APR 2022. Perception prioritized training of diffusion models. Cornell University arXiv:2204.00227v1.
- Dong, Wu & Zhou 2017. Xiao Dong, Jiasong Wu and Ling Zhou. 24 NOV 2017. Demystifying AlphaGo Zero as AlphaGo GAN. Cornell University arXiv:1711.09091v1.
- Edwards & Jackson 1993. G. B. Edwards and Robert R. Jackson. Use of prey-specific predatory behaviour by North American jumping spiders (Araneae, Salticidae) of the genus Phidippus. Journal of Zoology, London 229: 709-716.
- Esser, Romback & Ommer 2021. Patrick Esser, Robin Rombach and Bjo¨rn Ommer. 23 JUN 2021. Taming transformers for high-resolution image synthesis, v. 3. Cornell University arXiv:2012.09841v3.
- Goodfellow et al. 2014. Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 10 JUN 2014. Generative Adversarial Networks. Cornell University arXiv:1406.2661v1.
- Goodfellow et al. 2020. Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. NOV 2020. Generative Adversarial Networks. Communications of the ACM 63 (11): 139- 144.
- Gurney 1997. Kevin Gurney. An introduction to neural networks. UCL Press Limited, London.
- Hill 2022. David E. Hill. 23 AUG 2022. A salticid archetype for salticid spiders. Peckhamia 275.1: 1-39.
- Hill, Abhijith & Burini 2019. David E. Hill, Abhijith A. P. C. and Joao P. Burini. 6 FEB 2019. Do jumping spiders (Araneae: Salticidae) draw their own portraits? Peckhamia 179.1: 1-14.
- Hovannisyan et al. 2021. Mariam Hovhannisyan, Alex Clarke, Benjamin R. Geib, Rosalie Cicchinelli, Zachary Monge, Tory Worth, Amanda Szymanski, Roberto Cabeza and Simon W. Davis. 19 JAN 2021. The visual and semantic features that predict object memory: Concept property norms for 1,000 object images. Memory & Cognition 49: 712-731.
- Khan et al. 2022. Salman Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, Fahad Shahbaz Khan, and Mubarak Shah. 19 JAN 2022. Transformers in vision: a survey. Cornell University arXiv:2101.01169v5.
- Liu et al. 2017. Weibo Liu, Zidong Wang, Xiaohui Liu, Nianyin Zeng, Yurong Liu and Fuad E. Alsaadi. 19 APR 2017. A survey of deep neural network architectures and their applications. Neurocomputing 234: 11-26.
- Morizet 2020. Nicolas Moriset. Introduction to Generative Adversarial Networks. [Technical Report]. Advestis. 2020. hal- 02899937.
- Nichol et al. 2022. Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen. 8 MAR 2022. Towards photorealistic image generation and editing with text-guided diffusion models, v.3. Cornell University arXiv:2112.10741v3.
- Nielson 2019. Michael Nielson. Neural networks and deep learning, online at: http:// neuralnetworksanddeeplearning.com/
- Parmar et al. 2018. Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku and Dustin Tran. 15 JUN 2018. Image transformer. Cornell University arXiv:1802.05751v3. Proceedings of the 35 th International Conference on Machine Learning, Stockholm, Sweden, PMLR 80, 2018.
- Radford et. al 2021. Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. 26 FEB 2021. Learning transferable visual models from natural language supervision. Cornell University arXiv:2103.00020v1.
- Rajalingham et. al. 2018. R. Rajalingham, E. B. Issa, P. Bashivan, K. Kar, K. Schmidt and J. J. DiCarlo. Large scale, highresolution comparison of the core visual object recognition behavior of humans, monkeys, and state-of the art deep artifical neural networks. Journal of Neuroscience 38 (33): 7255-7269.
- Rombach et al. 2022. Robin Rombach, Andreas Blattman, Dominik Lorenz, Patrick Esser and Bjo¨rn Ommer. 13 APR 2022. High resolution image synthesis with latent diffusion models, v.2. Cornell University arXiv:2112.10752v2.
- Saharia et al. 2022. Chitwan Saharia, William Chan, Saurabh Saxenay, Lala Liy, Jay Whangy, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Hoy, David J Fleety, and Mohammad Norouzi. 3 MAY 2022. Photorealistic text-to-image diffusion models with deep language understanding. Cornell University arXiv:2205.11487v1.
- Vidya 2018. T. N. C. Vidya. 10 SEP 2018. Supernormal stimuli and responses. Resonance 23: 853-860.
- Zamorski et al. 2019. Maciej Zamorski, Adrian Zdobylak, Maciej Zieba and Jerzy Swiatek. 16 MAR 2019. Generative adversarial networks: recent developments. Cornell University arXiv:1903.12266v1.
- Wang et al. 2022. Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, and Mingyuan Zhou. 11 OCT 2022. Diffusion-GAN: training GANs with diffusion. Cornell University arXiv:2206.02262v3.
- Zeng & Kwong 2022. Chao Zeng and Sam Kwong. 23 MAR 2022. Learning transformer features for image quality assessment. Cornell University arXiv:2112.00485v2.