stephane-rivaud / ForwardLocalGradient
This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?
☆12Updated last year
Alternatives and similar repositories for ForwardLocalGradient:
Users that are interested in ForwardLocalGradient are comparing it to the libraries listed below
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆31Updated 2 years ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 2 years ago
- [ICLR 2021] "Long Live the Lottery: The Existence of Winning Tickets in Lifelong Learning" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, S…☆24Updated 3 years ago
- ICLR 2022 (Spolight): Continual Learning With Filter Atom Swapping☆15Updated last year
- ☆34Updated last year
- Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection☆21Updated 4 years ago
- Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint☆28Updated 2 years ago
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆27Updated 2 years ago
- Weight-Averaged Sharpness-Aware Minimization (NeurIPS 2022)☆28Updated 2 years ago
- ☆14Updated 3 years ago
- ☆35Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆26Updated last year
- Code for the paper "Efficient Dataset Distillation using Random Feature Approximation"☆37Updated last year
- [ICLR 2020] ”Triple Wins: Boosting Accuracy, Robustness and Efficiency Together by Enabling Input-Adaptive Inference“☆24Updated 3 years ago
- Training vision models with full-batch gradient descent and regularization☆37Updated 2 years ago
- Implementations of the algorithms described in the paper: On the Convergence Theory for Hessian-Free Bilevel Algorithms.☆10Updated 3 months ago
- Code release for REPAIR: REnormalizing Permuted Activations for Interpolation Repair☆46Updated last year
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆46Updated last year
- [ICML 2021] "Efficient Lottery Ticket Finding: Less Data is More" by Zhenyu Zhang*, Xuxi Chen*, Tianlong Chen*, Zhangyang Wang☆25Updated 3 years ago
- Codebase for the paper "A Gradient Flow Framework for Analyzing Network Pruning"☆21Updated 4 years ago
- ☆11Updated 2 years ago
- ☆38Updated 3 months ago
- Codes for the paper "Optimizing Mode Connectivity via Neuron Alignment" from NeurIPS 2020.☆16Updated 4 years ago
- On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]☆35Updated 3 years ago
- ☆57Updated 2 years ago
- Deep Learning & Information Bottleneck☆56Updated last year