Notes

• 2025-09-29-tbd-how-to-train-state-of-the-art-models-using-torchvision-s-latest-primitives
• 2025-09-29-tbd-trivialaugment-tuning-free-yet-state-of-the-art-data-augmentation
• 2025-09-29-tbd-when-does-label-smoothing-help
• 2025-10-05-tbd-an-image-is-worth-16x16-words-transformers-for-image-recognition-at-scale
• 2025-10-07-tbd-deep-residual-learning-for-image-recognition
• 2025-10-25-tbd-dropout-a-simple-way-to-prevent-neural-networks-from-overfitting
• 2025-11-02-tbd-batch-normalization-accelerating-deep-network-training-by-reducing-internal-covariate-shift
• 2025-11-04-tbd-cramming-training-a-language-model-on-a-single-gpu-in-one-day
• 2025-11-04-tbd-very-deep-convolutional-networks-for-large-scale-image-recognition