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Found 5 papers, 3 papers with code
SwiFT: Swin 4D fMRI Transformer
To address this challenge, we present SwiFT (Swin 4D fMRI Transformer), a Swin Transformer architecture that can learn brain dynamics directly from fMRI volumes in a memory and computation-efficient manner.
Towards More Robust Interpretation via Local Gradient Alignment
However, the lack of considering the normalization of the attributions, which is essential in their visualizations, has been an obstacle to understanding and improving the robustness of feature attribution methods.
DoPAMINE: Double-sided Masked CNN for Pixel Adaptive Multiplicative Noise Despeckling
We propose DoPAMINE, a new neural network based multiplicative noise despeckling algorithm.
Fooling Neural Network Interpretations via Adversarial Model Manipulation
We ask whether the neural network interpretation methods can be fooled via adversarial model manipulation, which is defined as a model fine-tuning step that aims to radically alter the explanations without hurting the accuracy of the original models, e. g., VGG19, ResNet50, and DenseNet121.
Subtask Gated Networks for Non-Intrusive Load Monitoring
In this work, we focus on the idea that appliances have on/off states, and develop a deep network for further performance improvements.
