helloyide / Cross-stitch-Networks-for-Multi-task-LearningLinks
A Tensorflow implementation of the paper arXiv:1604.03539
☆134Updated 7 years ago
Alternatives and similar repositories for Cross-stitch-Networks-for-Multi-task-Learning
Users that are interested in Cross-stitch-Networks-for-Multi-task-Learning are comparing it to the libraries listed below
Sorting:
- This in my Demo of Chen et al. "GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks" ICML 2018☆181Updated 4 years ago
- Learning deep representations by mutual information estimation and maximization☆322Updated 7 years ago
- extract features by maximizing mutual information☆148Updated 6 years ago
- This is a repository for Multi-task learning with toy data in Pytorch and Tensorflow☆137Updated 7 years ago
- Official Implementation of ICML 2019 Unsupervised label noise modeling and loss correction☆225Updated 5 years ago
- Virtual Adversarial Training (VAT) implementation for PyTorch☆296Updated 7 years ago
- MSc group project: Reproduction of 'Multi-Task Learning using Uncertainty to Weigh Losses for Scene Geometry and Semantics'; A. Kendall, …☆91Updated 6 years ago
- ☆130Updated 7 years ago
- The Simple and Efficient Semi-Supervised Learning Method for Deep Neural Networks☆342Updated 7 years ago
- PyTorch Implementation of the paper Learning to Reweight Examples for Robust Deep Learning☆354Updated 6 years ago
- Learning What and Where to Transfer (ICML 2019)☆250Updated 5 years ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆519Updated 4 years ago
- Virtual Adversarial Training (VAT) for semi-supervised MNIST written in PyTorch: https://arxiv.org/abs/1704.03976☆25Updated 6 years ago
- ☆148Updated 4 years ago
- Pytorch Implementation of Graph Convolutional Neural Networks☆111Updated 8 years ago
- Implementaion of Interpretable Convolutional Neural Networks with Dual Local and Global Attention for Review Rating Prediction☆123Updated 4 years ago
- PyTorch implementation of Temporal Ensembling for Semi-Supervised Learning☆110Updated 7 years ago
- This is a collection of Papers and Codes for Noisy Labels Problem.☆63Updated 7 years ago
- clustering☆115Updated 6 years ago
- [ICML 2020] Efficient Continuous Pareto Exploration in Multi-Task Learning☆149Updated 4 years ago
- Code for paper "Learning to Reweight Examples for Robust Deep Learning"☆270Updated 6 years ago
- Pytorch implementation of Virtual Adversarial Training☆134Updated 6 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 5 years ago
- [ICML2020] "Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training" by Xuxi Chen, Wuyang Chen, Tianlong Chen, Ye Yuan, Chen Gon…☆69Updated 4 years ago
- Official implementation of "Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning"☆155Updated 5 years ago
- Code release for "Learning Multiple Tasks with Multilinear Relationship Networks" (NIPS 2017)☆71Updated 8 years ago
- Tensorflow implementation of Capsule Graph Neural Network☆74Updated 4 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆291Updated 4 years ago
- official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)☆63Updated 5 years ago
- Pytorch implementation of the GradNorm. GradNorm addresses the problem of balancing multiple losses for multi-task learning by learning a…☆271Updated 3 years ago