XavierXiao / Likelihood-RegretLinks
Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020
☆50Updated 4 years ago
Alternatives and similar repositories for Likelihood-Regret
Users that are interested in Likelihood-Regret are comparing it to the libraries listed below
Sorting:
- Robust Out-of-distribution Detection in Neural Networks☆73Updated 3 years ago
- [SafeAI'21] Feature Space Singularity for Out-of-Distribution Detection.☆80Updated 4 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆36Updated 2 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago
- ☆57Updated 3 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆87Updated 3 years ago
- Last-layer Laplace approximation code examples☆83Updated 3 years ago
- Implementation of the paper "Understanding anomaly detection with deep invertible networks through hierarchies of distributions and featu…☆42Updated 4 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆143Updated 2 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆160Updated last year
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆71Updated 4 years ago
- ☆66Updated 5 years ago
- Out-of-distribution detection using the pNML regret. NeurIPS2021☆25Updated 8 months ago
- Metrics for out-of-distribution (OOD) detection performance evaluation☆48Updated 7 months ago
- Visual Representation Learning Benchmark for Self-Supervised Models☆35Updated last year
- This repository contains an official implementation of LPBNN.☆38Updated 2 years ago
- SSD: A Unified Framework for Self-Supervised Outlier Detection [ICLR 2021]☆137Updated 4 years ago
- Official Code Repository for La-MAML: Look-Ahead Meta-Learning for Continual Learning"☆77Updated 4 years ago
- Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection (https://arxiv.org/abs/2106.03004) by Stanis…☆44Updated 3 years ago
- ☆40Updated 5 years ago
- Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.☆137Updated 2 years ago
- Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.☆33Updated last year
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Official code for ICML 2022: Mitigating Neural Network Overconfidence with Logit Normalization☆150Updated 3 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆56Updated 3 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- A regularized self-labeling approach to improve the generalization and robustness of fine-tuned models☆27Updated 3 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated last year
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks☆231Updated 6 years ago
- Code for "Supermasks in Superposition"☆124Updated last year