Παραγωγικό αντιπαραθετικό δίκτυο (Greek Wikipedia)
Analysis of information sources in references of the Wikipedia article "Παραγωγικό αντιπαραθετικό δίκτυο" in Greek language version.
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arxiv.org
- Vondrick, Carl· Pirsiavash, Hamed· Torralba, Antonio (2016). «Generating Videos with Scene Dynamics». carlvondrick.com. arXiv:1609.02612
. Bibcode:2016arXiv160902612V.
cdotrends.com
- Wong, Ceecee. «The Rise of AI Supermodels». CDO Trends.
cern.ch
atlas.web.cern.ch
- ATLAS, Collaboration (2018). «Deep generative models for fast shower simulation in ATLAS».
cnet.com
- Mihalcik, Carrie (4 Οκτωβρίου 2019). «California laws seek to crack down on deepfakes in politics and porn». cnet.com. CNET. Ανακτήθηκε στις 13 Οκτωβρίου 2019.
columbia.edu
cs.columbia.edu
- Vondrick, Carl· Pirsiavash, Hamed· Torralba, Antonio (2016). «Generating Videos with Scene Dynamics». carlvondrick.com. arXiv:1609.02612 . Bibcode:2016arXiv160902612V.
courierpress.com
- Doyle, Michael (May 16, 2019). «John Beasley lives on Saddlehorse Drive in Evansville. Or does he?». Courier and Press. https://www.courierpress.com/story/news/crime/2019/05/16/john-beasley-lives-saddlehorse-drive-evansville-does-he/3700111002/.
doi.org
dx.doi.org
- Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Santhanam, Gokula Krishnan (2017-02-01). «Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit». Monthly Notices of the Royal Astronomical Society: Letters 467 (1): L110–L114. doi:. Bibcode: 2017MNRAS.467L.110S.
- Mustafa, Mustafa; Bard, Deborah; Bhimji, Wahid; Lukić, Zarija; Al-Rfou, Rami; Kratochvil, Jan M. (2019-05-06). «CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks». Computational Astrophysics and Cosmology 6 (1): 1. doi:. ISSN 2197-7909. Bibcode: 2019ComAC...6....1M.
- Paganini, Michela; de Oliveira, Luke; Nachman, Benjamin (2017). «Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics Synthesis». Computing and Software for Big Science 1: 4. doi:.
- Paganini, Michela; de Oliveira, Luke; Nachman, Benjamin (2018). «Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters». Phys. Rev. Letters 120 (4): 042003. doi:. PMID 29437460.
- Paganini, Michela; de Oliveira, Luke; Nachman, Benjamin (2018). «CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks». Phys. Rev. D 97: 014021. doi:.
- Erdmann, Martin; Glombitza, Jonas; Quast, Thorben (2019). «Precise Simulation of Electromagnetic Calorimeter Showers Using a Wasserstein Generative Adversarial Network». Computing and Software for Big Science 3: 4. doi:.
- Musella, Pasquale; Pandolfi, Francesco (2018). «Fast and Accurate Simulation of Particle Detectors Using Generative Adversarial Networks». Computing and Software for Big Science 2: 8. doi:. Bibcode: 2018arXiv180500850M.
- Zhavoronkov, Alex (2019). «Deep learning enables rapid identification of potent DDR1 kinase inhibitors». Nature Biotechnology 37 (9): 1038–1040. doi:. PMID 31477924.
forbes.com
- Dietmar, Julia. «GANs and Deepfakes Could Revolutionize The Fashion Industry». Forbes.
github.com
- Caesar, Holger (2019-03-01), A list of papers on Generative Adversarial (Neural) Networks: nightrome/really-awesome-gan, https://github.com/nightrome/really-awesome-gan, ανακτήθηκε στις 2019-03-02
harvard.edu
adsabs.harvard.edu
- Ho, Jonathon; Ermon, Stefano (2016). «Generative Adversarial Imitation Learning». Advances in Neural Information Processing Systems: 4565–4573. Bibcode: 2016arXiv160603476H. http://papers.nips.cc/paper/6391-generative-adversarial-imitation-learning.
- Luc, Pauline; Couprie, Camille; Chintala, Soumith; Verbeek, Jakob (2016-11-25). «Semantic Segmentation using Adversarial Networks». NIPS Workshop on Adversarial Training, Dec, Barcelona, Spain 2016. Bibcode: 2016arXiv161108408L.
- Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Santhanam, Gokula Krishnan (2017-02-01). «Generative Adversarial Networks recover features in astrophysical images of galaxies beyond the deconvolution limit». Monthly Notices of the Royal Astronomical Society: Letters 467 (1): L110–L114. doi:. Bibcode: 2017MNRAS.467L.110S.
- Mustafa, Mustafa; Bard, Deborah; Bhimji, Wahid; Lukić, Zarija; Al-Rfou, Rami; Kratochvil, Jan M. (2019-05-06). «CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks». Computational Astrophysics and Cosmology 6 (1): 1. doi:. ISSN 2197-7909. Bibcode: 2019ComAC...6....1M.
- Musella, Pasquale; Pandolfi, Francesco (2018). «Fast and Accurate Simulation of Particle Detectors Using Generative Adversarial Networks». Computing and Software for Big Science 2: 8. doi:. Bibcode: 2018arXiv180500850M.
- Tang, Xiaoou; Qiao, Yu; Loy, Chen Change; Dong, Chao; Liu, Yihao; Gu, Jinjin; Wu, Shixiang; Yu, Ke και άλλοι. (2018-09-01). «ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks» (στα αγγλικά). Bibcode: 2018arXiv180900219W.
- Vondrick, Carl· Pirsiavash, Hamed· Torralba, Antonio (2016). «Generating Videos with Scene Dynamics». carlvondrick.com. arXiv:1609.02612 . Bibcode:2016arXiv160902612V.
nih.gov
ncbi.nlm.nih.gov
- Paganini, Michela; de Oliveira, Luke; Nachman, Benjamin (2018). «Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multi-Layer Calorimeters». Phys. Rev. Letters 120 (4): 042003. doi:. PMID 29437460.
- Zhavoronkov, Alex (2019). «Deep learning enables rapid identification of potent DDR1 kinase inhibitors». Nature Biotechnology 37 (9): 1038–1040. doi:. PMID 31477924.
nips.cc
papers.nips.cc
- Ho, Jonathon; Ermon, Stefano (2016). «Generative Adversarial Imitation Learning». Advances in Neural Information Processing Systems: 4565–4573. Bibcode: 2016arXiv160603476H. http://papers.nips.cc/paper/6391-generative-adversarial-imitation-learning.
openai.com
- Andrej Karpathy; Pieter Abbeel; Greg Brockman; Peter Chen; Vicki Cheung; Rocky Duan; Ian Goodfellow; Durk Kingma και άλλοι., Generative Models, OpenAI, https://openai.com/blog/generative-models/, ανακτήθηκε στις April 7, 2016
phillipi.github.io
- Isola, Phillip; Zhu, Jun-Yan; Zhou, Tinghui; Efros, Alexei (2017). «Image-to-Image Translation with Conditional Adversarial Nets». Computer Vision and Pattern Recognition. https://phillipi.github.io/pix2pix/.
phys.org
- Kincade, Kathy (May 16, 2019). «CosmoGAN: Training a neural network to study dark matter». Phys.org. https://phys.org/news/2019-05-cosmogan-neural-network-dark.html.
rdmag.com
sciencedaily.com
- «Training a neural network to study dark matter». Science Daily. May 16, 2019. https://www.sciencedaily.com/releases/2019/05/190516145206.htm.
scientificamerican.com
- Greenemeier, Larry (20 Ιουνίου 2016). «When Will Computers Have Common Sense? Ask Facebook». Scientific American. Ανακτήθηκε στις 31 Ιουλίου 2016.
slashdot.org
tech.slashdot.org
- msmash (14 Φεβρουαρίου 2019). «'This Person Does Not Exist' Website Uses AI To Create Realistic Yet Horrifying Faces». Slashdot. Ανακτήθηκε στις 16 Φεβρουαρίου 2019.
technologyreview.com
- Knight, Will (Aug 7, 2018). «The Defense Department has produced the first tools for catching deepfakes». MIT Technology Review. https://www.technologyreview.com/s/611726/the-defense-department-has-produced-the-first-tools-for-catching-deepfakes/.
theregister.co.uk
- at 06:13, Katyanna Quach 20 May 2019. «Cosmoboffins use neural networks to build dark matter maps the easy way». www.theregister.co.uk (στα Αγγλικά). Ανακτήθηκε στις 20 Μαΐου 2019.
towardsdatascience.com
- Wei, Jerry (3 Ιουλίου 2019). «Generating Shoe Designs with Machine Learning». Medium (στα Αγγλικά). Ανακτήθηκε στις 6 Νοεμβρίου 2019.
wired.com
- Gregory, Barber. «A Molecule Designed By AI Exhibits 'Druglike' Qualities». Wired.
worldcat.org
- Mustafa, Mustafa; Bard, Deborah; Bhimji, Wahid; Lukić, Zarija; Al-Rfou, Rami; Kratochvil, Jan M. (2019-05-06). «CosmoGAN: creating high-fidelity weak lensing convergence maps using Generative Adversarial Networks». Computational Astrophysics and Cosmology 6 (1): 1. doi:. ISSN 2197-7909. Bibcode: 2019ComAC...6....1M.