YiteWang / NTK-SAP
[ICLR2023] NTK-SAP: Improving neural network pruning by aligning training dynamics
☆18Updated 2 years ago
Alternatives and similar repositories for NTK-SAP
Users that are interested in NTK-SAP are comparing it to the libraries listed below
Sorting:
- Deep Learning & Information Bottleneck☆60Updated last year
- [ICML2022] Training Your Sparse Neural Network Better with Any Mask. Ajay Jaiswal, Haoyu Ma, Tianlong Chen, ying Ding, and Zhangyang Wang☆28Updated 2 years ago
- ☆13Updated 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 3 years ago
- SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining (NeurIPS 2024)☆31Updated 6 months ago
- Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020☆28Updated 3 years ago
- [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, De…☆45Updated last year
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- ☆29Updated 11 months ago
- Code for Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot☆42Updated 4 years ago
- ☆21Updated 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…☆25Updated 3 years ago
- [ICML 2024] Junk DNA Hypothesis: A Task-Centric Angle of LLM Pre-trained Weights through Sparsity; Lu Yin*, Ajay Jaiswal*, Shiwei Liu, So…☆16Updated 3 weeks ago
- This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?☆12Updated last year
- A modern look at the relationship between sharpness and generalization [ICML 2023]☆43Updated last year
- [ICLR 2025] Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better☆14Updated 2 months ago
- Sharpness-Aware Minimization Leads to Low-Rank Features [NeurIPS 2023]☆28Updated last year
- source code for paper "Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models"☆25Updated 10 months ago
- Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).☆58Updated 3 years ago
- [ICLR 2023] 'Revisiting Pruning At Initialization Through The Lens of Ramanujan Graph" by Duc Hoang, Shiwei Liu, Radu Marculescu, Atlas W…☆13Updated last year
- Source code of "What can linearized neural networks actually say about generalization?☆20Updated 3 years ago
- ☆23Updated 2 years ago
- ☆15Updated last year
- [ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Di…☆57Updated 7 months ago
- Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection☆21Updated 4 years ago
- Structured Pruning Adapters in PyTorch☆17Updated last year
- Prospect Pruning: Finding Trainable Weights at Initialization Using Meta-Gradients☆31Updated 3 years ago
- [ICLR 2023] "Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!" Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen…☆28Updated last year
- ☆18Updated last year
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago