Code for the paper "Training CNNs with Selective Allocation of Channels" (ICML 2019)
☆25May 14, 2019Updated 6 years ago
Alternatives and similar repositories for selective-convolution
Users that are interested in selective-convolution are comparing it to the libraries listed below
Sorting:
- Lookahead: A Far-sighted Alternative of Magnitude-based Pruning (ICLR 2020)☆32Oct 25, 2020Updated 5 years ago
- [CVPR 2018] Official Tensorflow Code of Learning Strict Identity Mappings in Deep Residual Networks☆21Sep 27, 2020Updated 5 years ago
- Codes for "Learning bounds for risk-sensitive learning," NeurIPS 2020 (or see arXiv 2006.08138)☆11Oct 15, 2020Updated 5 years ago
- ProxylessNAS-Pytorch☆24Aug 9, 2019Updated 6 years ago
- [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“☆24Dec 30, 2021Updated 4 years ago
- PyTorch implementation of Group Normalization https://arxiv.org/abs/1803.08494☆11Mar 23, 2018Updated 7 years ago
- Hybrid Binary Networks: Optimizing for Accuracy, Efficiency and Memory - WACV18☆12Jul 5, 2019Updated 6 years ago
- ☆22Jul 27, 2019Updated 6 years ago
- ☆47Dec 26, 2019Updated 6 years ago
- ☆12Apr 16, 2020Updated 5 years ago
- Codes for DATA: Differentiable ArchiTecture Approximation.☆11Jul 22, 2021Updated 4 years ago
- ☆15Jan 8, 2020Updated 6 years ago
- ☆25Jun 5, 2019Updated 6 years ago
- ☆13Jan 8, 2020Updated 6 years ago
- Code for BlockSwap (ICLR 2020).☆33Mar 25, 2021Updated 4 years ago
- Successfully training approximations to full-rank matrices for efficiency in deep learning.☆17Jan 5, 2021Updated 5 years ago
- pytorch implementation of "Contrastive Multiview Coding", "Momentum Contrast for Unsupervised Visual Representation Learning", and "Unsup…☆18Mar 23, 2020Updated 5 years ago
- Code for LIT, ICML 2019☆20Jun 11, 2019Updated 6 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆36Jul 3, 2021Updated 4 years ago
- Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks☆18Nov 5, 2019Updated 6 years ago
- ☆14Jun 5, 2020Updated 5 years ago
- PyTorch implementation for OD-cheap-convolution.☆20Sep 29, 2019Updated 6 years ago
- AutoML framework balancing performance and complexity☆15May 9, 2021Updated 4 years ago
- ☆38Nov 4, 2024Updated last year
- Pytorch code for paper: Full-Stack Filters to Build Minimum Viable CNNs☆16Sep 10, 2019Updated 6 years ago
- ☆20Oct 3, 2019Updated 6 years ago
- ☆16Nov 12, 2019Updated 6 years ago
- Code for the paper "Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data" at ICML 2019.☆20Apr 22, 2019Updated 6 years ago
- Mining GOLD Samples for Conditional GANs (NeurIPS 2019)☆17Oct 22, 2019Updated 6 years ago
- Role-Wise Data Augmentation for Knowledge Distillation☆19Nov 22, 2022Updated 3 years ago
- MiLeNAS: Efficient Neural Architecture Search via Mixed-Level Reformulation. Published in CVPR 2020☆36Dec 17, 2020Updated 5 years ago
- Algorithms for curriculum learning. The code of the "Mastering Rate based Curriculum Learning" paper.☆20Jul 25, 2019Updated 6 years ago
- Local search for NAS☆18Nov 3, 2020Updated 5 years ago
- ☆19May 28, 2020Updated 5 years ago
- Global Sparse Momentum SGD for pruning very deep neural networks☆44Sep 8, 2022Updated 3 years ago
- PyTorch implementation of A Lightweight Encoder-Decoder Path for Deep Residual Networks.☆19Dec 10, 2019Updated 6 years ago
- Neural Rejuvenation: Improving Deep Network Training by Enhancing Computational Resource Utilization at CVPR'19☆48Jun 13, 2019Updated 6 years ago
- Regularizing Meta-Learning via Gradient Dropout☆53Apr 14, 2020Updated 5 years ago
- PyTorch implementation of shake-drop regularization☆55Apr 24, 2020Updated 5 years ago