Implementation for "Conditional entropy minimization principle for learning domain invariant representation features".
The code is reproduced from this repo at https://github.com/ahujak/IB-IRM.
Please see the guideline for running in each sub-dataset folder.
Requirements:
torch 1.6.0
torchvision 0.7.0
numpy 1.19.1
tqdm 4.41.1
torch-max-mem This package provides decorators for memory utilization maximization with PyTorch and CUDA by starting with a maximum parameter size and
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Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distribution.
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