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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Abinaya Manimaran, Thiyagarajan Ramanathan, Suya You |
| 2019 |
| arxiv 1902.09107 |
| Fixup Initialization: Residual Learning Without Normalization | Hongyi Zhang, Yann N. Dauphin, Tengyu Ma | 2019 | arxiv 1901.09321 |
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| A Deep Learning Interpretable Classifier for Diabetic Retinopathy Disease Grading | Jordi de la Torre, Aida Valls, Domenec Puig | 2017 | arxiv 1712.08107 |
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| Joint Learning of Neural Networks via Iterative Reweighted Least Squares | Zaiwei Zhang, Xiangru Huang, Qixing Huang | 2019 | arxiv 1905.06526 |
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| Deep multi-class learning from label proportions | Gabriel Dulac-Arnold, Neil Zeghidour, Marco Cuturi | 2019 | arxiv 1905.12909 |
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| Security for Distributed Deep Neural Networks Towards Data Confidentiality & Intellectual Property Protection | Laurent Gomez, Marcus Wilhelm, José Márquez | 2019 | arxiv 1907.04246 |
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| Defending Against Universal Perturbations With Shared Adversarial Training | Chaithanya Kumar Mummadi, Thomas Brox, Jan Hendrik Metzen | 2018 | arxiv 1812.03705 |
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| Deep Dictionary Learning: A PARametric NETwork Approach | Shahin Mahdizadehaghdam, Ashkan Panahi, Hamid Krim | 2018 | arxiv 1803.04022 |
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| Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output | Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay | 2019 | arxiv 1910.10307 |
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| Parting with Illusions about Deep Active Learning | Sudhanshu Mittal, Maxim Tatarchenko, Özgün Çiçek | 2019 | arxiv 1912.05361 |
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