Research graph
References from Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation. Local targets link to admitted publications; unresolved targets remain external evidence.
Denoising diffusion probabilistic models
External reference
10.52202/068431-2011
10.52202/068431-2011 · External reference
Trustworthy AI: A computational perspective
10.1145/3546872 · 2022 · External reference
10.1561/3300000041
10.1561/3300000041 · External reference
10.1007/s11263-024-02117-4
10.1007/s11263-024-02117-4 · External reference
Visualizing data using t-SNE
2008 · External reference
Energy-based out-of-distribution detection
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10.1109/tpami.2023.3328883
10.1109/tpami.2023.3328883 · External reference
On the importance of gradients for detecting distributional shifts in the wild
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10.1109/tpami.2024.3459988
10.1109/tpami.2024.3459988 · External reference
React: Out-of-distribution detection with rectified activations
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Out-of-distribution detection with deep nearest neighbors
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10.1109/iccv51070.2023.01780
10.1109/iccv51070.2023.01780 · External reference
10.52202/068431-1509
10.52202/068431-1509 · External reference
10.52202/075280-1260
10.52202/075280-1260 · External reference
Extremely simple activation shaping for out-of-distribution detection
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Scaling for training time and post-hoc out-of-distribution detection enhancement
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10.1109/cvpr52733.2024.02473
10.1109/cvpr52733.2024.02473 · External reference
10.1109/cvpr52729.2023.01901
10.1109/cvpr52729.2023.01901 · External reference
10.52202/068431-1300
10.52202/068431-1300 · External reference
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
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Mahalanobis : Improving OOD detection via feature normalization
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10.1109/iccv51070.2023.00162
10.1109/iccv51070.2023.00162 · External reference
Out-of-distribution detection based on in-distribution data patterns memorization with modern Hopfield energy
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10.1109/tkde.2024.3468629
10.1109/tkde.2024.3468629 · External reference
Out-of-distribution detection with subspace techniques and probabilistic modeling of features
2020 · External reference
10.1109/cvpr46437.2021.00933
10.1109/cvpr46437.2021.00933 · External reference
10.1007/bfb0020217
10.1007/bfb0020217 · External reference
10.1162/089976698300017467
10.1162/089976698300017467 · External reference
10.1109/cvpr.2009.5206848
10.1109/cvpr.2009.5206848 · External reference
10.1080/14786440109462720
10.1080/14786440109462720 · External reference
10.1002/wics.101
10.1002/wics.101 · External reference
Random features for large-scale kernel machines
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Using the Nyström method to speed up kernel machines
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10.52202/079017-4268
10.52202/079017-4268 · External reference
10.1002/9781118165621
10.1002/9781118165621 · External reference
Learning multiple layers of features from tiny images
2009 · External reference
LSUN: Construction of a large-scale image dataset using deep learning with humans in the loop
2015 · External reference
10.1109/tpami.2017.2723009
10.1109/tpami.2017.2723009 · External reference
10.1007/978-1-4757-2711-1
10.1007/978-1-4757-2711-1 · External reference
On the Nyström method for approximating a gram matrix for improved kernel-based learning
2005 · External reference
Sampling methods for the Nyström method
2012 · External reference
Randomized nonlinear component analysis
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Streaming kernel PCA with $\mathcal {O}(\sqrt{n})$O(n) random features
2018 · External reference
Gain with no pain: Efficiency of kernel-PCA by Nyström sampling
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Kernel PCA with the Nyström method
2021 · External reference
10.1214/22-aos2204
10.1214/22-aos2204 · External reference
Statistical optimality and computational efficiency of Nystrom kernel PCA
2022 · External reference
10.1109/tnn.2004.837781
10.1109/tnn.2004.837781 · External reference
10.1109/tpami.2024.3520899
10.1109/tpami.2024.3520899 · External reference
10.1109/cvpr.2016.90
10.1109/cvpr.2016.90 · External reference
10.1109/cvpr.2018.00474
10.1109/cvpr.2018.00474 · External reference
An image is worth 16 x 16 words: Transformers for image recognition at scale
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10.1109/cvpr.2018.00914
10.1109/cvpr.2018.00914 · External reference
10.1109/cvpr.2010.5539970
10.1109/cvpr.2010.5539970 · External reference
10.1109/cvpr.2014.461
10.1109/cvpr.2014.461 · External reference
Supervised contrastive learning
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
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Scaling out-of-distribution detection for real-world settings
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Enhancing the reliability of out-of-distribution image detection in neural networks
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10.1109/cvpr52688.2022.00487
10.1109/cvpr52688.2022.00487 · External reference
10.1109/cvpr52729.2023.00330
10.1109/cvpr52729.2023.00330 · External reference
SSD: A unified framework for self-supervised outlier detection
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PyTorch: An imperative style, high-performance deep learning library
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10.1007/978-3-031-20053-3_40
10.1007/978-3-031-20053-3_40 · External reference
10.52202/075280-1659
10.52202/075280-1659 · External reference
10.1109/tbdata.2019.2921572
10.1109/tbdata.2019.2921572 · External reference
10.1145/2487575.2487591
10.1145/2487575.2487591 · External reference
Uncertainty estimation using a single deep deterministic neural network
External reference
10.1016/j.patcog.2006.07.009
10.1016/j.patcog.2006.07.009 · External reference
10.1109/cvpr42600.2020.01096
10.1109/cvpr42600.2020.01096 · External reference
10.1007/978-3-031-72624-8_26
10.1007/978-3-031-72624-8_26 · External reference
10.1109/cvpr52729.2023.01507
10.1109/cvpr52729.2023.01507 · External reference
10.1109/iccv51070.2023.00488
10.1109/iccv51070.2023.00488 · External reference
10.1109/iccv51701.2025.00335
10.1109/iccv51701.2025.00335 · External reference
10.1007/s11263-024-02156-x
10.1007/s11263-024-02156-x · External reference
Unsupervised out-of-distribution detection with diffusion inpainting
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CSI: Novelty detection via contrastive learning on distributionally shifted instances
External reference
10.52202/068431-2696
10.52202/068431-2696 · External reference
10.1609/aaai.v36i7.20752
10.1609/aaai.v36i7.20752 · External reference
10.1016/j.artint.2024.104275
10.1016/j.artint.2024.104275 · External reference
10.1109/tpami.2023.3321869
10.1109/tpami.2023.3321869 · External reference
10.1109/tpami.2021.3097011
10.1109/tpami.2021.3097011 · External reference
10.1016/j.patcog.2022.109057
10.1016/j.patcog.2022.109057 · External reference
Nyström method vs random Fourier features: A theoretical and empirical comparison
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10.1073/pnas.1903070116
10.1073/pnas.1903070116 · External reference
10.1016/j.artint.2022.103803
10.1016/j.artint.2022.103803 · External reference
Learning in feature spaces via coupled covariances: Asymmetric kernel SVD and Nyström method
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10.1609/aaai.v35i16.17664
10.1609/aaai.v35i16.17664 · External reference
Nyström method for accurate and scalable implicit differentiation
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