Companion code for the research paper "CoAug: Combining Augmentation of Labels and Labeling Rules"
-
Updated
Jun 21, 2024 - Python
Companion code for the research paper "CoAug: Combining Augmentation of Labels and Labeling Rules"
This is the code accompanying the AAAI 2022 paper "Ranking Info Noise Contrastive Estimation: Boosting Contrastive Learning via Ranked Positives" https://arxiv.org/abs/2201.11736 . The method allows you to use additional ranking information for representation learning.
Official Implementation of the paper "Multi-Attribute Open Set Recognition" (GCPR 2022)
Official Implementation of the paper "Overcoming Shortcut Learning in a Target Domain by Generalizing Basic Visual Factors from a Source Domain" (ECCV 2022)
Code accompanying the ICLR 2021 paper "ResNet After All? Neural ODEs and Their Numerical Solution"
Coder of the paper 'Latent Outlier Exposure for Anomaly Detectin with Contaminated Data' published in ICML 2022
BCAI ART : Bosch Center for AI Adversarial Robustness Toolkit
[CVPR 2022] What Matters For Meta-Learning Vision Regression Tasks?
Code of the paper 'Neural Transformation Learning for Anomaly Detection' published in ICML 2021
Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)
Source code for Bechtold et al., "Fostering Generalization in Single-view 3D Reconstruction by Learning a Hierarchy of Local and Global Shape Priors", CVPR 2021.
This will be the companion code for the benchmarking study reported in the paper Transfer Learning with Gaussian Processes for Bayesian Optimization accepted for publication at AISTATS 2022
Resources related to our paper "CLIN-X: pre-trained language models and a study on cross-task transfer for concept extraction in the clinical domain"
Resources related to IberLEF 2021 paper "Boosting Transformers for Job Expression Extraction and Classification in a Low-Resource Setting"
Resources related to EMNLP 2021 paper "To Share or not to Share: Predicting Sets of Sources for Model Transfer Learning"
Resources related to EMNLP 2021 paper "FAME: Feature-Based Adversarial Meta-Embeddings for Robust Input Representations"
Companion code for the work presented in “Training Object Detectors if Only Large Objects are Labeled” (Accepted at BMVC 2021)
Code for the 2021 paper "Negation-Instance Based Evaluation of End-to-End Negation Resolution"
Add a description, image, and links to the paper-resource topic page so that developers can more easily learn about it.
To associate your repository with the paper-resource topic, visit your repo's landing page and select "manage topics."