dlmacedo / robust-deep-learning
A project to train your model from scratch or fine-tune a pretrained model using the losses provided in this library to improve out-of-distribution detection and uncertainty estimation performances. Calibrate your model to produce enhanced uncertainty estimations. Detect out-of-distribution data using the defined score type and threshold.
☆17Updated 2 years ago
Alternatives and similar repositories for robust-deep-learning:
Users that are interested in robust-deep-learning are comparing it to the libraries listed below
- This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer☆40Updated 3 years ago
- A project to improve out-of-distribution detection (open set recognition) and uncertainty estimation by changing a few lines of code in y…☆45Updated 2 years ago
- [MIDL 2023] Official Imeplementation of "Making Your First Choice: To Address Cold Start Problem in Vision Active Learning"☆35Updated last year
- [Re] Can gradient clipping mitigate label noise? (ML Reproducibility Challenge 2020)☆14Updated 7 months ago
- A project to add scalable state-of-the-art out-of-distribution detection (open set recognition) support by changing two lines of code! Pe…☆75Updated 2 years ago
- PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations☆16Updated 4 years ago
- Code for ECCV 2022 paper "DICE: Leveraging Sparsification for Out-of-Distribution Detection"☆40Updated 2 years ago
- Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch☆52Updated 4 years ago
- Official Pytorch Implementation of: "Semantic Diversity Learning for Zero-Shot Multi-label Classification"(ICCV, 2021) paper☆30Updated 2 years ago
- [SafeAI'21] Feature Space Singularity for Out-of-Distribution Detection.☆80Updated 4 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated last year
- Github for the conference paper GLOD-Gaussian Likelihood OOD detector☆16Updated 2 years ago
- Code of our method MbLS (Margin-based Label Smoothing) for network calibration. To Appear at CVPR 2022. Paper : https://arxiv.org/abs/211…☆50Updated 2 years ago
- (ICML 2021) Implementation for S2SD - Simultaneous Similarity-based Self-Distillation for Deep Metric Learning. Paper Link: https://arxiv…☆42Updated 4 years ago
- ☆46Updated 4 years ago
- Learning Loss for Active Learning Pytorch Implementation,(reproduction)☆32Updated 5 years ago
- ☆35Updated 2 years ago
- Un-offical PyTorch Implementation of "Class-Balanced Distillation for Long-Tailed Visual Recognition" paper.☆17Updated 3 years ago
- Github code for the paper Maximum Class Separation as Inductive Bias in One Matrix. Arxiv link: https://arxiv.org/abs/2206.08704☆29Updated last year
- Robust Contrastive Learning Using Negative Samples with Diminished Semantics (NeurIPS 2021)☆38Updated 3 years ago
- DiWA: Diverse Weight Averaging for Out-of-Distribution Generalization☆29Updated 2 years ago
- This repository includes the official project of L2B, from our paper "Learning to Bootstrap for Combating Label Noise".☆32Updated 2 weeks ago
- Official code and data for NeurIPS 2023 paper "ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial …☆37Updated last year
- ☆31Updated 3 years ago
- ☆16Updated last year
- Code for Overinterpretation paper☆19Updated last year
- Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection (https://arxiv.org/abs/2106.03004) by Stanis…☆43Updated 3 years ago
- [NeurIPS 2021] “Improving Contrastive Learning on Imbalanced Data via Open-World Sampling”, Ziyu Jiang, Tianlong Chen, Ting Chen, Zhangya…☆28Updated 3 years ago
- A regularized self-labeling approach to improve the generalization and robustness of fine-tuned models☆28Updated 2 years ago
- ☆29Updated last year