1-33 of about 33 matches for site:arxiv.org searching
https://arxiv.org/abs/1710.05941
1710.05941] Searching for Activation Functions Skip to main content We gratefully acknowledge support from
http://arxiv.org/abs/0810.3966
0810.3966] Searching for Cost Optimized Interstellar Beacons Skip to main content We gratefully acknowledge
https://arxiv.org/abs/0810.3966
0810.3966] Searching for Cost Optimized Interstellar Beacons Skip to main content We gratefully acknowledge
https://arxiv.org/html/1709.00645
2017 Asteroseismology and Exoplanets: Listening to the Stars and Searching for New
https://arxiv.org/abs/1910.07969
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[1910.04760] A cost-effective method for improving and re-purposing large, pre-trained GANs by fine-
https://arxiv.org/abs/1910.04760
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https://arxiv.org/abs/2001.05027
2 other authors View PDF Abstract: Image retrieval is the problem of searching an image database for
https://arxiv.org/abs/2406.09408
the model would fail to reproduce the same output. Unfortunately, directly searching for these
https://arxiv.org/abs/2406.09408
the model would fail to reproduce the same output. Unfortunately, directly searching for these
https://arxiv.org/abs/2001.05027
2 other authors View PDF Abstract: Image retrieval is the problem of searching an image database for
https://arxiv.org/abs/2311.17984
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https://arxiv.org/abs/2012.09855
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https://arxiv.org/abs/2503.12855
a framework to enhance existing VideoQA datasets with evidence reasoning chains, automatically constructed by searching for optimal
https://arxiv.org/abs/2308.12419
model via multi-task training. To address the problem of searching for fingerspelled
https://arxiv.org/abs/cs/0105030
Set and the associated controlled vocabularies facilitate consistent description and focussed searching. We report progress on
https://arxiv.org/abs/1704.05473
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https://arxiv.org/abs/2411.07763
show that solving problems in Spider 2.0 frequently requires understanding and searching through database metadata, dialect
[2306.16221] The NANOGrav 15-year Data Set: Search for Anisotropy in the Gravitational-Wave Backgrou
https://arxiv.org/abs/2306.16221
anisotropy. We end by highlighting the opportunities and challenges in searching for anisotropy
https://arxiv.org/abs/1906.05370
Instead of using thousands of cores for weeks, NGE efficiently solves searching problem within a
https://arxiv.org/abs/1906.05370
Instead of using thousands of cores for weeks, NGE efficiently solves searching problem within a
https://arxiv.org/abs/2010.04029
critical to learn. Existing methods either suffer from the problem of searching in a
https://arxiv.org/abs/2106.04004
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https://arxiv.org/abs/2408.05284
Such bounds could be used to reject potentially dangerous actions. Our main results involve searching for cautious
https://arxiv.org/abs/1205.4788
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