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Narine Kokhlikyan
Narine Kokhlikyan
Meta AI
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Cited by
Year
Captum: A unified and generic model interpretability library for PyTorch. arXiv 2020
N Kokhlikyan, V Miglani, M Martin, E Wang, B Alsallakh, J Reynolds, ...
arXiv preprint arXiv:2009.07896, 0
713
Mind the Pad--CNNs Can Develop Blind Spots
B Alsallakh, N Kokhlikyan, V Miglani, J Yuan, O Reblitz-Richardson
arXiv preprint arXiv:2010.02178, 2020
882020
Pytorch captum
N Kokhlikyan, V Miglani, M Martin, E Wang, J Reynolds, A Melnikov, ...
GitHub repository, 2019
502019
Instantiating resources of an IT-service
JE Arwe, G Breiter, M Chodorowski, F Dross, N Kokhlikyan, HA Le, ...
US Patent 9,203,774, 2015
282015
Xair: A framework of explainable ai in augmented reality
X Xu, A Yu, TR Jonker, K Todi, F Lu, X Qian, JM Evangelista Belo, T Wang, ...
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems …, 2023
262023
Investigating saturation effects in integrated gradients
V Miglani, N Kokhlikyan, B Alsallakh, M Martin, O Reblitz-Richardson
arXiv preprint arXiv:2010.12697, 2020
232020
Captum: A unified and generic model interpretability library for PyTorch. arXiv
N Kokhlikyan, V Miglani, M Martin, E Wang, B Alsallakh, J Reynolds, ...
arXiv preprint arXiv:2009.07896, 2020
212020
Instantiating resources of an IT-service
JE Arwe, G Breiter, M Chodorowski, F Dross, N Kokhlikyan, HA Le, ...
US Patent 9,432,247, 2016
142016
Method cards for prescriptive machine-learning transparency
D Adkins, B Alsallakh, A Cheema, N Kokhlikyan, E McReynolds, P Mishra, ...
Proceedings of the 1st International Conference on AI Engineering: Software …, 2022
132022
Prescriptive and descriptive approaches to machine-learning transparency
D Adkins, B Alsallakh, A Cheema, N Kokhlikyan, E McReynolds, P Mishra, ...
CHI conference on human factors in computing systems extended abstracts, 1-9, 2022
122022
Investigating sanity checks for saliency maps with image and text classification
N Kokhlikyan, V Miglani, B Alsallakh, M Martin, O Reblitz-Richardson
arXiv preprint arXiv:2106.07475, 2021
122021
A unified and generic model interpretability library for pytorch
N Kokhlikyan, V Miglani, M Martin, E Wang, B Alsallakh, J Reynolds, ...
arXiv preprint arXiv:2009.07896, 2020
122020
Debugging the internals of convolutional networks
B Alsallakh, N Kokhlikyan, V Miglani, S Muttepawar, E Wang, S Zhang, ...
eXplainable AI approaches for debugging and diagnosis., 2021
112021
Filtering electronic messages
C Sathi, A Tarasov, D Mykhaylov, N Kokhlikyan, R Ivchenko
US Patent 10,447,635, 2019
112019
Using captum to explain generative language models
V Miglani, A Yang, AH Markosyan, D Garcia-Olano, N Kokhlikyan
arXiv preprint arXiv:2312.05491, 2023
102023
Building recommender systems with PyTorch
D Mudigere, M Naumov, J Spisak, G Chauhan, N Kokhlikyan, A Singh, ...
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
82020
Fine-grained interpretation and causation analysis in deep NLP models
H Sajjad, N Kokhlikyan, F Dalvi, N Durrani
arXiv preprint arXiv:2105.08039, 2021
72021
Instantiating resources of an IT-service
JE Arwe, G Breiter, M Chodorowski, F Dross, N Kokhlikyan, HA Le, ...
US Patent 9,515,866, 2016
52016
PyTorch Captum. 2019
N Kokhlikyan, V Miglani, M Martin, E Wang, J Reynolds, A Melnikov, ...
URL: https://github. com/pytorch/captum, 0
5
Mind the pool: Convolutional neural networks can overfit input size
B Alsallakh, D Yan, N Kokhlikyan, V Miglani, O Reblitz-Richardson, ...
The Eleventh International Conference on Learning Representations, 2022
32022
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