slowbull / DDG
A PyTorch implementation of the paper "Decoupled Parallel Backpropagation with Convergence Guarantee"
☆29Updated 6 years ago
Alternatives and similar repositories for DDG:
Users that are interested in DDG are comparing it to the libraries listed below
- ☆30Updated 4 years ago
- Net2Net implementation on PyTorch for any possible vision layers.☆38Updated 7 years ago
- SmoothOut: Smoothing Out Sharp Minima to Improve Generalization in Deep Learning☆23Updated 6 years ago
- ☆74Updated 5 years ago
- SNIP: SINGLE-SHOT NETWORK PRUNING☆30Updated last month
- Code for "Picking Winning Tickets Before Training by Preserving Gradient Flow" https://openreview.net/pdf?id=SkgsACVKPH☆103Updated 5 years ago
- [ICLR 2019] ProbGAN: Towards Probabilistic GAN with Theoretical Guarantees☆32Updated 5 years ago
- Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".☆62Updated 5 years ago
- Zero-Shot Knowledge Distillation in Deep Networks☆65Updated 3 years ago
- Compressing Neural Networks using the Variational Information Bottleneck☆65Updated 2 years ago
- ☆70Updated 5 years ago
- ☆83Updated 5 years ago
- PyTorch Code for "Evaluating the search phase of Neural Architecture Search" @ ICLR 2020☆50Updated 5 years ago
- Code for paper "Continual and Multi-Task Architecture Search (ACL 2019)"☆41Updated 5 years ago
- Code release to reproduce ASHA experiments from "Random Search and Reproducibility for NAS."☆22Updated 5 years ago
- ☆18Updated 5 years ago
- Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934☆112Updated 5 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Implementation of soft parameter sharing for neural networks☆69Updated 4 years ago
- A compressed adaptive optimizer for training large-scale deep learning models using PyTorch☆27Updated 5 years ago
- Cheap distillation for convolutional neural networks.☆33Updated 6 years ago
- Code for BlockSwap (ICLR 2020).☆33Updated 4 years ago
- "Layer-wise Adaptive Rate Scaling" in PyTorch☆86Updated 4 years ago
- ☆21Updated 5 years ago
- Implementation of ICLR 2017 paper "Loss-aware Binarization of Deep Networks"☆18Updated 6 years ago
- Code to reproduce some of the figures in the paper "On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima"☆139Updated 7 years ago
- [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“☆24Updated 3 years ago
- ☆65Updated 4 years ago
- ☆34Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago