This is a list of peer-reviewed representative papers on deep learning dynamics (optimization dynamics of neural networks). The success of deep learning attributes to both network architecture and stochastic optimization. Thus, deep learning dynamics play an essentially important role in theoretical foundation of deep learning.
☆305Apr 10, 2024Updated 2 years ago
Alternatives and similar repositories for deep-learning-dynamics-paper-list
Users that are interested in deep-learning-dynamics-paper-list are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- [ICML 2022, Oral] The PyTorch Implementation of Adaptive Inertia Methods. The algorithms are based on our paper: "Adaptive Inertia: Dise…☆150Feb 17, 2023Updated 3 years ago
- [ICML 2021] The official PyTorch Implementations of Positive-Negative Momentum Optimizers.☆28Aug 30, 2022Updated 4 years ago
- [Neural Computation, MIT Press] The PyTorch Implementation of Variable Optimizers/ Neural Variable Risk Minimization proposed in our Neur…☆33Aug 3, 2021Updated 5 years ago
- [NeurIPS 2023] The PyTorch Implementation of Scheduled (Stable) Weight Decay.☆61Feb 3, 2024Updated 2 years ago
- Welcome to the Awesome Feature Learning in Deep Learning Thoery Reading Group! This repository serves as a collaborative platform for sch…☆210Apr 13, 2026Updated 5 months ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- [KDD 2023] code for "Test accuracy vs. generalization gap: model selection in NLP without accessing training or testing data" https://arx…☆12Oct 17, 2022Updated 3 years ago
- Neural Tangent Kernel Papers☆122Jan 12, 2025Updated last year
- Welcome to the 'In Context Learning Theory' Reading Group☆31Nov 8, 2024Updated last year
- This framework implements key experiments on the sparse double descent phenomenon (ICML 2022).☆15Dec 13, 2022Updated 3 years ago
- PyHessian is a Pytorch library for second-order based analysis and training of Neural Networks☆795Jul 10, 2025Updated last year
- Codebase for the paper "A Gradient Flow Framework for Analyzing Network Pruning"☆20Jan 31, 2021Updated 5 years ago
- ☆10Dec 17, 2019Updated 6 years ago
- ☆14Oct 18, 2021Updated 4 years ago
- The official code of "Mano: Restriking Manifold Optimization for LLM Training".☆25Jun 1, 2026Updated 3 months ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- An implementation of the penalty-based bilevel gradient descent (PBGD) algorithm and the iterative differentiation (ITD/RHG) methods.☆20Feb 13, 2023Updated 3 years ago
- ☆15May 2, 2026Updated 4 months ago
- A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...☆410Aug 18, 2026Updated last month
- ☆29Jun 12, 2025Updated last year
- A curated list of awesome papers on dataset reduction, including dataset distillation (dataset condensation) and dataset pruning (coreset…☆62Jan 14, 2025Updated last year
- Visualization of mean field and neural tangent kernel regime☆23Jul 25, 2024Updated 2 years ago
- ScalingOpt - Optimization Community☆108Sep 19, 2026Updated last week
- Efficient empirical NTKs in PyTorch☆22Jun 13, 2022Updated 4 years ago
- Official implementation for the paper "Controlled Sparsity via Constrained Optimization"☆12Aug 10, 2022Updated 4 years ago
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- [NeurIPS 2023 Spotlight] Temperature Balancing, Layer-wise Weight Analysis, and Neural Network Training☆37Apr 7, 2025Updated last year
- ☆35Dec 5, 2022Updated 3 years ago
- Quantification of Uncertainties in Neural Networks☆11Aug 29, 2026Updated 3 weeks ago
- ☆95Jul 18, 2023Updated 3 years ago
- SOLNP+: A derivative-free optimization software☆24May 13, 2025Updated last year
- Awesome papers in machine learning theory☆10Feb 12, 2022Updated 4 years ago
- Repository for the paper "Interpreting Temporal Graph Neural Networks with Koopman Theory"☆12Apr 7, 2026Updated 5 months ago
- [NeurIPS 2021] code for "Taxonomizing local versus global structure in neural network loss landscapes" https://arxiv.org/abs/2107.11228☆20Jan 7, 2022Updated 4 years ago
- ☆27Feb 2, 2023Updated 3 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- ☆23Nov 1, 2022Updated 3 years ago
- Deep Learning Theory and Practice☆25Dec 5, 2023Updated 2 years ago
- ☆36Jun 13, 2023Updated 3 years ago
- Code for Paper (Policy Optimization in RLHF: The Impact of Out-of-preference Data)☆29Dec 19, 2023Updated 2 years ago
- [NeurIPS 2026] Piecewise Sparse Attention Is Wiser for Efficient Diffusion Transformers☆44Jul 1, 2026Updated 2 months ago
- SE-PINN: Solving the Schrödinger Equation via Physics-Informed Machine Learning☆11Dec 17, 2025Updated 9 months ago
- Finetune Google's pre-trained ViT models from HuggingFace's model hub.☆19Apr 4, 2021Updated 5 years ago