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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Transfer Learning with Neural AutoML |
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| Catherine Wong, Neil Houlsby, Yifeng Lu |
| 2018 |
| arxiv 1803.02780 |
| Deep Residual Learning in the JPEG Transform Domain | Max Ehrlich, Larry Davis | 2018 | arxiv 1812.11690 |
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| Blink: Fast and Generic Collectives for Distributed ML | Guanhua Wang, Shivaram Venkataraman, Amar Phanishayee | 2019 | arxiv 1910.04940 |
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| An Intelligent Remote Sensing Image Quality Inspection System | Yijiong Yu, Tao Wang, Kang Ran | 2023 | arxiv 2307.11965 |
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| Offline Writer Identification Using Convolutional Neural Network Activation Features | Vincent Christlein, David Bernecker, Andreas Maier | 2024 | arxiv 2402.17029 |
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| The Susceptibility of Example-Based Explainability Methods to Class Outliers | Ikhtiyor Nematov, Dimitris Sacharidis, Tomer Sagi | 2024 | arxiv 2407.20678 |
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| Deep Learning Classification With Noisy Labels | Guillaume Sanchez, Vincente Guis, Ricard Marxer | 2020 | arxiv 2004.11116 |
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| Data Pruning via Separability, Integrity, and Model Uncertainty-Aware Importance Sampling | Steven Grosz, Rui Zhao, Rajeev Ranjan | 2024 | arxiv 2409.13915 |
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| Stochastic Resonance Improves the Detection of Low Contrast Images in Deep Learning Models | Siegfried Ludwig | 2025 | arxiv 2502.14442 |
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| A Continual Learning Framework for Adaptive Defect Classification and Inspection | Wenbo Sun, Raed Al Kontar, Judy Jin | 2022 | arxiv 2203.08796 |
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