Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Naresh, Iyer"'
Autor:
Santamaria-Pang, Alberto, Qiu, Jianwei, Chowdhury, Aritra, Kubricht, James, Tu, Peter, Naresh, Iyer, Virani, Nurali
We propose a novel framework for real-time black-box universal attacks which disrupts activations of early convolutional layers in deep learning models. Our hypothesis is that perturbations produced in the wavelet space disrupt early convolutional la
Externí odkaz:
http://arxiv.org/abs/2107.12473
Publikováno v:
Annual Conference of the PHM Society. 14
Free-form text-based maintenance and service records related to industrial assets capture the observations and actions of service engineers and are a crucial resource for assessing system-level asset health. To facilitate tracking of historical asset
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa8862f75ac5226ba47ececd297000ef
https://doi.org/10.36001/phmconf.2022.v14i1.3159
https://doi.org/10.36001/phmconf.2022.v14i1.3159
Publikováno v:
AAAI
With the advent of Deep Learning, the field of machine learning (ML) has surpassed human-level performance on diverse classification tasks. At the same time, there is a stark need to characterize and quantify reliability of a model's prediction on in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c0b051a8a7ae346c3ea03df7e5428ea2
https://doi.org/10.1609/aaai.v34i04.6071
https://doi.org/10.1609/aaai.v34i04.6071
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030863616
ICANN (1)
ICANN (1)
The rapid and accurate prediction of residual stresses in metal additive manufacturing (3D printing) processes is crucial to ensuring defect-free fabrication of parts used in critical industrial applications. This paper presents promising outcomes fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed909bed28531c6eadb65d4d0a283919
https://doi.org/10.1007/978-3-030-86362-3_15
https://doi.org/10.1007/978-3-030-86362-3_15
Publikováno v:
ICIP
Machine learning models provide statistically impressive results which might be individually unreliable. To provide reliability, we propose an Epistemic Classifier (EC) that can provide justification of its belief using support from the training data
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f984e08d7240c2e59c1190c042047b2
https://doi.org/10.1109/icip40778.2020.9190836
https://doi.org/10.1109/icip40778.2020.9190836
Autor:
Elena Meyer, Naresh Iyer, Alireza Shahkarami, Oscar Becerra Moreno, Glen Murrell, Meagan Friedrichs, Robert Klenner, Ghazal Izadi
Publikováno v:
Day 1 Mon, May 04, 2020.
Inflow Control Devices (ICDs) help reduce the adverse consequences of uneven inflow issues in a lateral completion system. The most common uneven inflow consequences are early water breakthrough and gas coning in water-driven and saturated reservoirs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38c4fb57a23dfa80c18c1d100e0f30c5
https://doi.org/10.4043/30716-ms
https://doi.org/10.4043/30716-ms
Publikováno v:
Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II.
In machine learning, backdoor or trojan attacks during model training can cause the targeted model to deceptively learn to misclassify in the presence of specific triggers. This mechanism of deception enables the attacker to exercise full control on
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41333677365396a8ad2949aa20caa17d
https://doi.org/10.1117/12.2558255
https://doi.org/10.1117/12.2558255
Autor:
Naresh Iyer, Nurali Virani, Glen Murrell, Hayley Stephenson, Alireza Shahkarami, Guoxiang Liu, Robert Klenner, Brian Chandler Barr
Publikováno v:
Day 1 Tue, April 09, 2019.
Optimization problems, such as optimal well-spacing or completion design, can be resolved rapidly via surrogate proxy models, and these models can be built using either data-based or physics-based methods. Each approach has its strengths and weakness
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d820d2ff7bf6b153baa5531c162d1853
https://doi.org/10.2118/195238-ms
https://doi.org/10.2118/195238-ms
Autor:
Rob Klenner, Naresh Iyer, Anveshi Charuvaka, Nurali Virani, Hayley Stephenson, Guoxiang Liu, Glen Murrell
Publikováno v:
Day 2 Thu, September 06, 2018.
Frac hits are a form of fracture-driven interference (FDI) that occur when newly drilled wells communicate with existing wells during completion, and which may negatively or positively affect production. An analytics and machine-learning approach is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71189aef20df1f5708dc9f4761f80b05
https://doi.org/10.2118/191789-ms
https://doi.org/10.2118/191789-ms
Publikováno v:
Proceedings of the 5th Unconventional Resources Technology Conference.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ed669ec352285d88c0945d424ea4fd8
https://doi.org/10.15530/urtec-2017-2673695
https://doi.org/10.15530/urtec-2017-2673695