Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Grimes, Keltin"'
Machine learning models are vulnerable to adversarial attacks, including attacks that leak information about the model's training data. There has recently been an increase in interest about how to best address privacy concerns, especially in the pres
Externí odkaz:
http://arxiv.org/abs/2405.19211
Autor:
Casper, Stephen, Yun, Jieun, Baek, Joonhyuk, Jung, Yeseong, Kim, Minhwan, Kwon, Kiwan, Park, Saerom, Moore, Hayden, Shriver, David, Connor, Marissa, Grimes, Keltin, Nicolson, Angus, Tagade, Arush, Rumbelow, Jessica, Nguyen, Hieu Minh, Hadfield-Menell, Dylan
Interpretability techniques are valuable for helping humans understand and oversee AI systems. The SaTML 2024 CNN Interpretability Competition solicited novel methods for studying convolutional neural networks (CNNs) at the ImageNet scale. The object
Externí odkaz:
http://arxiv.org/abs/2404.02949
Autor:
Sorcar, Saurav, Hwang, Yunju, Lee, Jaewoong, Kim, Hwapyong, Grimes, Keltin M., Grimes, Craig A., Jung, Jin-Woo, Cho, Chang-Hee, Majima, Tetsuro, Hoffmann, Michael R., In, Su-Il
If we wish to sustain our terrestrial ecosphere as we know it, then reducing the concentration of atmospheric CO_2 is of critical importance. An ideal pathway for achieving this would be the use of sunlight to recycle CO_2, in combination with water,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od________38::308a2c2f0fc21d54c417be016c73ba25
https://resolver.caltech.edu/CaltechAUTHORS:20190521-104010002
https://resolver.caltech.edu/CaltechAUTHORS:20190521-104010002
Autor:
Sorcar, Saurav, Hwang, Yunju, Lee, Jaewoong, Kim, Hwapyong, Grimes, Keltin M., Grimes, Craig A., Jung, Jin-Woo, Cho, Chang-Hee, Majima, Tetsuro, Hoffmann, Michael R., In, Su-Il
Publikováno v:
Energy & Environmental Science; Sep2019, Vol. 12 Issue 9, p2685-2696, 12p
