10 citations · 10 across the 1 of their papers we have counts for
3 papers
Memory Efficient 3D U-Net with Reversible Mobile Inverted Bottlenecks for Brain Tumor Segmentation
Mihir Pendse, Vithursan Thangarasa, Vitaliy Chiley +3
We propose combining memory saving techniques with traditional U-Net architectures to increase the complexity of the models on the Brain Tumor Segmentation (BraTS) challenge. The B…
Enabling Continual Learning with Differentiable Hebbian Plasticity
Vithursan Thangarasa, Thomas Miconi, Graham W. Taylor
Continual learning is the problem of sequentially learning new tasks or knowledge while protecting previously acquired knowledge. However, catastrophic forgetting poses a grand cha…
Self-Paced Learning with Adaptive Deep Visual Embeddings
Vithursan Thangarasa, Graham W. Taylor
Selecting the most appropriate data examples to present a deep neural network (DNN) at different stages of training is an unsolved challenge. Though practitioners typically ignore…