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In an out-of-distribution (OOD) detection problem, samples of known classes(also called in-distribution classes) are used to train a special classifier.
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Contrastive training for improved out-of-distribution detection
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Breaking the closed world assumption in text classification
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He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Hendrycks, D.; and Gimpel, K. 2016 · 2016
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Professor forcing: A new algorithm for training recurrent networks
Lamb, A. M.; Goyal, A. G. A. P.; Zhang, Y.; Zhang, S.; Courville, A. C.; and Bengio, Y. 2016 · 2016
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Outlier detection with autoencoder ensembles
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
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Unseen class discovery in open-world classification
Shu, L.; Xu, H.; and Liu, B. 2018 · 2018
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Adam: A Method for Stochastic Optimization
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Training confidence-calibrated classifiers for detecting out-of-distribution samples
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Enhancing the reliability of out-of-distribution image detection in neural networks
Liang, S.; Li, Y.; and Srikant, R. 2017 · 2017
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Doc: Deep open classification of text documents
Shu, L.; Xu, H.; and Liu, B. 2017 · 2017
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Attention is all you need
Vaswani, A.; Shazeer, N.; Parmar, N.; Uszkoreit, J.; Jones, L.; Gomez, A. N.; Kaiser, Ł.; and Polosukhin, I. 2017 · 2017
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C2ae: Class conditioned auto-encoder for open-set recognition
Oza, P.; and Patel, V. M. 2019 · 2019
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Open-world learning and application to product classification
Xu, H.; Liu, B.; Shu, L.; and Yu, P. 2019 · 2019
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Generalized odin: Detecting out-of-distribution image without learning from out-of-distribution data
Hsu, Y.-C.; Shen, Y.; Jin, H.; and Kira, Z. 2020 · 2020
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Generative-discriminative feature representations for open-set recognition
Perera, P.; Morariu, V. I.; Jain, R.; Manjunatha, V.; Wigington, C.; Ordonez, V.; and Patel, V. M. 2020 · 2020
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Transformers: State-of-the-Art Natural Language Processing
Wolf, T.; Debut, L.; Sanh, V.; Chaumond, J.; Delangue, C.; Moi, A.; Cistac, P.; Rault, T.; Louf, R.; Funtowicz, M.; Davison, J.; Shleifer, S.; von Platen, P.; Ma, C.; Jernite, Y.; Plu, J.; Xu, C.; Scao, T. L.; Gugger, S.; Drame, M.; Lhoest, Q.; and Rush, A. M. 2020 · 2020
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Exploring the Limits of Out-of-Distribution Detection
Fort, S.; Ren, J.; and Lakshminarayanan, B. 2021 · 2021
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Class Anchor Clustering: A Loss for Distance-Based Open Set Recognition
Miller, D.; Sunderhauf, N.; Milford, M.; and Dayoub, F. 2021 · 2021
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Learning transferable visual models from natural language supervision
Radford, A.; Kim, J. W.; Hallacy, C.; Ramesh, A.; Goh, G.; Agarwal, S.; Sastry, G.; Askell, A.; Mishkin, P.; Clark, J.; et al. 2021 · 2021
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ODIST: Open World Classification via Distributionally Shifted Instances
Shu, L.; Benajiba, Y.; Mansour, S.; and Zhang, Y. 2021 · 2021
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