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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| Improvising the Learning of Neural Networks on Hyperspherical Manifold | Lalith Bharadwaj Baru, Sai Vardhan Kanumolu, Akshay Patel Shilhora | 2021 | arxiv 2109.14746 |
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| Interpreting Bias in the Neural Networks: A Peek Into Representational Similarity | Gnyanesh Bangaru, Lalith Bharadwaj Baru, Kiran Chakravarthula | 2022 | arxiv 2211.07774 |
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| Local Magnification for Data and Feature Augmentation | Kun He, Chang Liu, Stephen Lin | 2022 | arxiv 2211.07859 |
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| A Comprehensive Survey of Transformers for Computer Vision | Sonain Jamil, Md. Jalil Piran, Oh-Jin Kwon | 2022 | arxiv 2211.06004 |
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| How to Combine Variational Bayesian Networks in Federated Learning | Atahan Ozer, Kadir Burak Buldu, Abdullah Akgül | 2022 | arxiv 2206.10897 |
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| Contrastive Losses Are Natural Criteria for Unsupervised Video Summarization | Zongshang Pang, Yuta Nakashima, Mayu Otani | 2022 | arxiv 2211.10056 |
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| Can a face tell us anything about an NBA prospect? -- A Deep Learning approach | Andreas Gavros, Foteini Gavrou | 2022 | arxiv 2212.06804 |
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| Regularization with Latent Space Virtual Adversarial Training | Genki Osada, Budrul Ahsan, Revoti Prasad Bora | 2020 | arxiv 2011.13181 |
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| UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs | Philipp Oberdiek, Gernot A. Fink, Matthias Rottmann | 2022 | arxiv 2201.13279 |
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| Image-Based Vehicle Classification by Synergizing Features from Supervised and Self-Supervised Learning Paradigms | Shihan Ma, Jidong J. Yang | 2023 | arxiv 2302.00648 |
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