AlexMeinke / Provable-OOD-DetectionLinks
Guarantees on the behavior of neural networks don't always have to come at the cost of performance.
☆28Updated 2 years ago
Alternatives and similar repositories for Provable-OOD-Detection
Users that are interested in Provable-OOD-Detection are comparing it to the libraries listed below
Sorting:
- A way to achieve uniform confidence far away from the training data.☆38Updated 4 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆42Updated 4 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated last month
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆36Updated 3 years ago
- Out-of-distribution Detection via Generation - NeurIPS 2019☆18Updated 5 years ago
- Code for "Bridging the Gap between f-GANs and Wasserstein GANs", ICML 2020☆14Updated 5 years ago
- Code for the paper "Semi-Conditional Normalizing Flows for Semi-Supervised Learning"☆10Updated 5 years ago
- Provable Worst Case Guarantees for the Detection of Out-of-Distribution Data☆13Updated 2 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- ICML 2020, Estimating Generalization under Distribution Shifts via Domain-Invariant Representations☆23Updated 5 years ago
- Robust Out-of-distribution Detection in Neural Networks☆73Updated 3 years ago
- Learning perturbation sets for robust machine learning☆65Updated 3 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- Fine-grained ImageNet annotations☆29Updated 5 years ago
- This code reproduces the results of the paper, "Measuring Data Leakage in Machine-Learning Models with Fisher Information"☆50Updated 3 years ago
- ☆25Updated 5 years ago
- Codebase for Learning Invariances in Neural Networks☆95Updated 2 years ago
- ☆58Updated 3 years ago
- In this paper, we show that the performance of a learnt generative model is closely related to the model's ability to accurately represen…☆41Updated 4 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated last year
- Official Implementation of Remembering for the Right Reasons (ICLR 2021)☆30Updated 3 years ago
- ☆34Updated 4 years ago
- Last-layer Laplace approximation code examples☆82Updated 3 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- [NeurIPS 2020] Coresets for Robust Training of Neural Networks against Noisy Labels☆34Updated 4 years ago
- CIFAR-5m dataset☆39Updated 4 years ago
- Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.☆33Updated last year
- CVPR'19 experiments with (on-manifold) adversarial examples.☆45Updated 5 years ago