The length of your blogpost should be 1000-1500 words excluding references.
The deadline for submission is two weeks after your presentation.
- A robust deep neural network for denoising task-based fMRI data: An application to working memory and episodic memory
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
- Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach
- Automatic detection of rare pathologies in fundus photographs using few-shot learning
- Curriculum Loss: Robust Learning and Generalization against Label Corruption
- Data Augmentation Using Learned Transformations for One-Shot Medical Image Segmentation
- Explaining Neural Networks Semantically and Quantitatively
- f-AnoGAN: Fast unsupervised anomaly detection with generative adversarial networks
- FastAutoAugment
- Image-to-Images Translation for Multi-Task Organ Segmentation and Bone Suppression in Chest X-Ray Radiography
- Meta-Learning Update Rules For Unsupervised Representation Learning
- MixMatch: A Holistic Approach to Semi-Supervised Learning
- Multi-task learning for the segmentation of organs at risk with label dependence
- Restricting the flow: Information bottlenecks for attribution
- Search for Better Students to Learn Distilled Knowledge
- Temporal Cycle-Consistency Learning
- Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps
- Understanding deep networks via extremal perturbations and smooth masks
- Unsupervised X-ray image segmentation with task driven generative adversarial networks