| Anomaly Detection with Density Estimation |
2020 |
|
| Normalizing Flows for Probabilistic Modeling and Inference |
2021 |
|
| Sylvester Normalizing Flows for Variational Inference |
2018 |
|
| Neural Spline Flows |
2019 |
|
| Residual Flows for Invertible Generative Modeling |
2020 |
|
| Deep Residual Flow for Novelty Detection |
2020 |
|
| Do Deep Generative Models Know What They Don't Know? |
2019 |
|
| WAIC, but Why? Generative Ensembles for Robust Anomaly Detection |
2019 |
|
| Towards Out-of-Distribution Detection with Divergence Guarantee in Deep Generative Models |
2019 |
|
| Out-of-Distribution Detection with Distance Guarantee in Deep Generative Models |
2021 |
|
| Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder |
2020 |
|
| Block Neural Autoregressive Flow |
2019 |
|
| MaCow: Masked Convolutional Generative Flow |
2019 |
|
| Normalizing Flows for Probabilistic Modeling and Inference |
2021 |
|
| Artificial Neural Networks Applied to Taxi Destination Prediction |
2015 |
|
| Deep Generative Models Strike Back! Improving Understanding and Evaluation in Light of Unmet Expectations for OoD Data |
2019 |
|
| Likelihood Assignment for Out-of-Distribution Inputs in Deep Generative Models is Sensitive to Prior Distribution Choice |
2019 |
|
| Rethinking Assumptions in Deep Anomaly Detection |
2021 |
|
| The Expressive Power of a Class of Normalizing Flow Models |
2020 |
|
| Graphical Normalizing Flows |
2021 |
|
| Why Normalizing Flows Fail to Detect Out-of-Distribution Data |
2020 |
|
| Robust model training and generalisation with Studentising flows |
2020 |
|
| Deep Learning for Anomaly Detection: A Review |
2020 |
|
| SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows |
2020 |
|
| Semi-supervised Learning with Deep Generative Models |
2014 |
|
| Semi-Supervised Learning with Normalizing Flows |
2019 |
|
| Semi-Conditional Normalizing Flows for Semi-Supervised Learning |
2020 |
|
| OneFlow: One-class flow for anomaly detection based on a minimal volume region |
2021 |
|
| A Survey on Anomaly Detection for Technical Systems using LSTM Networks |
2021 |
|
| Likelihood Ratios for Out-of-Distribution Detection |
2019 |
|
| A Unifying Review of Deep and Shallow Anomaly Detection |
2021 |
|
| Understanding Failures in Out-of-Distribution Detection with Deep Generative Models |
2021 |
|
| An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series |
2021 |
|
| Fully Convolutional Cross-Scale-Flows for Image-based Defect Detection |
2021 |
|
| NFAD: fixing anomaly detection using normalizing flows |
2021 |
|
| Principal Manifold Flows |
2022 |
|
| PAC Guarantees and Effective Algorithms for Detecting Novel Categories |
2022 |
|
| Reward Once, Penalize Once: Rectifying Time Series Anomaly Detection |
2022 |
|