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pro vyhledávání: '"Sharma, Charchit"'
Autor:
Ramachandran, Rahul, Kulkarni, Tejal, Sharma, Charchit, Vijaykeerthy, Deepak, Balasubramanian, Vineeth N
Evaluating models and datasets in computer vision remains a challenging task, with most leaderboards relying solely on accuracy. While accuracy is a popular metric for model evaluation, it provides only a coarse assessment by considering a single mod
Externí odkaz:
http://arxiv.org/abs/2409.04041
Autor:
Reddy, Abbavaram Gowtham, Bachu, Saketh, Dash, Saloni, Sharma, Charchit, Sharma, Amit, Balasubramanian, Vineeth N
Counterfactual data augmentation has recently emerged as a method to mitigate confounding biases in the training data. These biases, such as spurious correlations, arise due to various observed and unobserved confounding variables in the data generat
Externí odkaz:
http://arxiv.org/abs/2305.18183
Autor:
Reddy, Abbavaram Gowtham, Bachu, Saketh, Dash, Saloni, Sharma, Charchit, Sharma, Amit, Balasubramanian, Vineeth N
Counterfactual data augmentation has recently emerged as a method to mitigate confounding biases in the training data for a machine learning model. These biases, such as spurious correlations, arise due to various observed and unobserved confounding
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::59c7972e3f94deb0f36ec3c7487c4cd5
http://arxiv.org/abs/2305.18183
http://arxiv.org/abs/2305.18183