Bit Error Robustness in PyTorch Article Series
I was planning to have an article series on bit error robustness in deep learning — similar to my article series on adversarial robustness — with accompanying PyTorch code. However, the recent progress in machine learning made me focus on other projects. Nevertheless, the articles should have been:
- Simple Fixed-Point Quantization for DNNs in PyTorch
- 4.5% Test Error on CIFAR10 with 4-Bit Fixed-Point Quantization
- Implementing Fast Bitwise Operations for PyTorch
- Testing Robustness Against Bit Errors in Quantized DNN Weights
- Weight Clipping for Improved Bit Error Robustness
- Random Bit Error Training in PyTorch
-  D. Stutz, N. Chandramoorthy, M. Hein, B. Schiele. Bit Error Robustness for Energy-Efficient DNN Accelerators. MLSys, 2021.
-  D. Stutz, N. Chandramoorthy, M. Hein, B. Schiele. Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators. TPAMI, 2022.