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Out-of-distribution (OOD) detection is critical when deploying machine learning models in the real world.
Scaling out-of-distribution detection for real-world settings
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
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Sehwag, V., Chiang, M., and Mittal, P · 2021
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Diversified outlier exposure for out-of-distribution detection via informative extrapolation
Zhu, J., Geng, Y., Yao, J., Liu, T., Niu, G., Sugiyama, M., and Han, B · 2021
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Hendrycks, D. and Gimpel, K · 2017
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Attention is all you need
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Lee, K., Lee, K., Lee, H., and Shin, J · 2018
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Umap: Uniform manifold approximation and projection for dimension reduction
McInnes, L., Healy, J., and Melville, J · 2018
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Representation learning with contrastive predictive coding
Oord, A. v. d., Li, Y., and Vinyals, O · 2018
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Four Shapes
smeschke · 2018
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The inaturalist species classification and detection dataset
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Du, X., Wang, Z., Cai, M., and Li, Y · 2022
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CLOOB: Modern Hopfield networks with InfoLOOB outperform clip
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Hendrycks, D., Zou, A., Mazeika, M., Tang, L., Li, B., Song, D., and Steinhardt, J · 2022
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POEM: Out-of-distribution detection with posterior sampling
Ming, Y., Fan, Y., and Li, Y · 2022
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Provable guarantees for understanding out-of-distribution detection
Morteza, P. and Li, Y · 2022
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History compression via language models in reinforcement learning
Paischer, F., Adler, T., Patil, V., Bitto-Nemling, A., Holzleitner, M., Lehner, S., Eghbal-Zadeh, H., and Hochreiter, S · 2022
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Towards total recall in industrial anomaly detection
Roth, K., Pemula, L., Zepeda, J., Schölkopf, B., Brox, T., and Gehler, P · 2022
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Statistical properties of the log-cosh loss function used in machine learning
Saleh, R. A. and Saleh, A · 2022
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CLOOME: a new search engine unlocks bioimaging databases for queries with chemical structures
Sanchez-Fernandez, A., Rumetshofer, E., Hochreiter, S., and Klambauer, G · 2022
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Hopular: Modern Hopfield networks for tabular data
Schäfl, B., Gruber, L., Bitto-Nemling, A., and Hochreiter, S · 2022
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Out-of-distribution detection with deep nearest neighbors
Sun, Y., Ming, Y., Zhu, X., and Li, Y · 2022
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Vim: Out-of-distribution with virtual-logit matching
Wang, H., Li, Z., Feng, L., and Zhang, W · 2022
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Openood: Benchmarking generalized out-of-distribution detection
Yang, J., Wang, P., Zou, D., Zhou, Z., Ding, K., Peng, W., Wang, H., Chen, G., Li, B., Sun, Y., et al · 2022
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Conformal prediction for time series with modern hopfield networks
Auer, A., Gauch, M., Klotz, D., and Hochreiter, S · 2023
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Extremely simple activation shaping for out-of-distribution detection
Djurisic, A., Bozanic, N., Ashok, A., and Liu, R · 2023
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Gen: Pushing the limits of softmax-based out-of-distribution detection
Liu, X., Lochman, Y., and Zach, C · 2023
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How to exploit hyperspherical embeddings for out-of-distribution detection?
Ming, Y., Sun, Y., Dia, O., and Li, Y · 2023
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Energy-based cross attention for Bayesian context update in text-to-image diffusion models
Park, G. Y., Kim, J., Kim, B., Lee, S. W., and Ye, J. C · 2023
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Context-enriched molecule representations improve few-shot drug discovery
Schimunek, J., Seidl, P., Friedrich, L., Kuhn, D., Rippmann, F., Hochreiter, S., and Klambauer, G · 2023
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Non-parametric outlier synthesis
Tao, L., Du, X., Zhu, X., and Li, Y · 2023
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The faiss library
Douze, M., Guzhva, A., Deng, C., Johnson, J., Szilvasy, G., Mazaré, P.-E., Lomeli, M., Hosseini, L., and Jégou, H · 2024
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Outlier-efficient hopfield layers for large transformer-based models
Hu, J. Y.-C., Chang, P.-H., Luo, H., Chen, H.-Y., Li, W., Wang, W.-P., and Liu, H · 2024
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DOS: Diverse outlier sampling for out-of-distribution detection
Jiang, W., Cheng, H., Chen, M., Wang, C., and Wei, H · 2024
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Learning with mixture of prototypes for out-of-distribution detection
Lu, H., Gong, D., Wang, S., Xue, J., Yao, L., and Moore, K · 2024
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Scaling for training time and post-hoc out-of-distribution detection enhancement
Xu, K., Chen, R., Franchi, G., and Yao, A · 2024
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