reconstruction error

Non-linear, Sparse Dimensionality Reduction via Path Lasso Penalized Autoencoders JMLR 2021 RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection IJCAI 2021 Time Series Anomaly Detection with Multiresolution Ensemble Decoding AAAI 2021 Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error IJCAI 2020 Learning Memory-Guided Normality for Anomaly Detection CVPR 2020 Lipschitz Continuous Autoencoders in Application to Anomaly Detection AISTATS 2020 Memory-Efficient Learning of Stable Linear Dynamical Systems for Prediction and Control NeurIPS 2020 Robustness of Autoencoders for Anomaly Detection Under Adversarial Impact IJCAI 2020 C2AE: Class Conditioned Auto-Encoder for Open-Set Recognition CVPR 2019 Forward-Backward Generative Adversarial Networks for Anomaly Detection ACML 2019 Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection ICCV 2019 Non-Autoregressive Machine Translation with Auxiliary Regularization AAAI 2019 Novelty Detection for Multispectral Images with Application to Planetary Exploration AAAI 2019 Partial Label Learning with Unlabeled Data IJCAI 2019 Robust Principal Component Analysis with Adaptive Neighbors NeurIPS 2019 Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers CVPR 2019 Unsupervised Feature Selection by Pareto Optimization AAAI 2019 Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection ICLR 2018 Efficient DNN Neuron Pruning by Minimizing Layer-wise Nonlinear Reconstruction Error IJCAI 2018 Future Frame Prediction for Anomaly Detection – A New Baseline CVPR 2018 Supervised autoencoders: Improving generalization performance with unsupervised regularizers NeurIPS 2018 The Price of Fair PCA: One Extra dimension NeurIPS 2018 Angle Principal Component Analysis IJCAI 2017 Reconstruct & Crush Network NeurIPS 2017 Reconstruction-based Unsupervised Feature Selection: An Embedded Approach IJCAI 2017