Implementation of Attention-based Deep Multiple Instance Learning in PyTorch
Role in this project:
ML Engineer Contributions:16 commits, 8 PRs, 13 pushes in 4 years 1 month
Contributions summary:Max contributed to the implementation of an Attention-based Deep Multiple Instance Learning model. Their work includes adding and modifying files related to data loading, model definition (specifically the Attention mechanism), and training scripts. The user implemented training and testing functionality, including loss calculation and error metrics, within the context of a PyTorch framework for MNIST bags example. Additionally, the user made minor adjustments such as changing print statements and merging branches.
deep-learningpytorchattention-mechanismmultiple-instance-learning
Contributions:29 commits, 27 pushes, 1 branch in 2 months