Benutzer:C.heck

Links

adversarial attacks

• https://bdtechtalks.com/2019/04/02/ai-nlp-paraphrasing-adversarial-attacks/
• https://bdtechtalks.com/2019/04/02/ai-nlp-paraphrasing-adversarial-attacks/
• https://boingboing.net/2019/03/31/mote-in-cars-eye.html
• https://venturebeat.com/2019/04/01/text-based-ai-models-are-vulnerable-to-paraphrasing-attacks-researchers-find/
• https://spectrum.ieee.org/cars-that-think/transportation/self-driving/three-small-stickers-on-road-can-steer-tesla-autopilot-into-oncoming-lane

HowTo's

• https://cv-tricks.com/how-to/breaking-deep-learning-with-adversarial-examples-using-tensorflow/
• https://medium.com/@ml.at.berkeley/tricking-neural-networks-create-your-own-adversarial-examples-a61eb7620fd8

libraries

• https://github.com/bethgelab
• https://github.com/tensorflow/cleverhans

https://towardsdatascience.com/know-your-enemy-7f7c5038bdf3

https://medium.com/@AINowInstitute/the-10-top-recommendations-for-the-ai-field-in-2017-b3253624a7

XAI

• https://de.m.wikipedia.org/wiki/Explainable_Artificial_Intelligence
• https://netzpolitik.org/2018/enquete-kommission-kuenstliche-intelligenz-sachverstaendige-und-abgeordnete-klaeren-grundbegriffe/
• https://www.ayasdi.com/blog/artificial-intelligence/trust-challenge-explainable-ai-not-enough/
• https://www.bons.ai/blog/explainable-artificial-intelligence-using-model-induction
• https://en.m.wikipedia.org/wiki/Right_to_explanation

ethics

• https://www.economist.com/science-and-technology/2018/02/15/computer-programs-recognise-white-men-better-than-black-women
• https://books.google.de/books?id=rLsyDwAAQBAJ&pg=PA95&redir_esc=y#v=onepage&q&f=false
• https://books.google.de/books?id=_H1K3vojDFQC&pg=PA762&redir_esc=y#v=onepage&q&f=false
• https://neil.fraser.name/writing/tank/
• https://www.wired.com/story/why-ai-is-still-waiting-for-its-ethics-transplant/

last semester

Datei:Neuronales-netz am eigenen-bild.ipynb