code of the CVPR 2020 paper "Learning to Optimize on SPD Manifolds"
☆13Sep 12, 2020Updated 5 years ago
Alternatives and similar repositories for Learning-to-optimize-on-SPD-manifolds
Users that are interested in Learning-to-optimize-on-SPD-manifolds are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- (CVPR24) Riemannian Multinomial Logistics Regression for SPD Neural Networks☆15Feb 5, 2025Updated last year
- Four commonly used operations on the symmetric positive definite manifold☆29Jul 8, 2022Updated 3 years ago
- ☆13Sep 14, 2022Updated 3 years ago
- ☆15May 29, 2023Updated 3 years ago
- Motif-aware Riemannian Graph Neural Network with Generative-Contrastive Learning☆19Apr 15, 2024Updated 2 years ago
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- A powerful automation agent for macOS that enables natural language control of various system applications and services. This agent allow…☆60Jun 5, 2025Updated last year
- In this project, we implemented 7 interpretation techniques on two benchmark deep learning models "EEGNet" and "InterpretableCNN" for EEG…☆17Mar 15, 2022Updated 4 years ago
- ☆14Mar 19, 2024Updated 2 years ago
- This is an unofficial PyTorch implementation for paper "A Riemannian Network for SPD Matrix Learning", AAAI 2017☆39Oct 12, 2018Updated 7 years ago
- ☆13Oct 31, 2021Updated 4 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆60Sep 28, 2021Updated 4 years ago
- 数学建模相关资料☆10Jul 10, 2023Updated 2 years ago
- [NeurIPS 2022] Source code for our paper "Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data"☆25Oct 16, 2023Updated 2 years ago
- A new model for quickly training and simulating adaptive leaky integrate-and-fire spiking neural networks.☆14Apr 9, 2024Updated 2 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Repository for the SPDTransNet model, a Transformer-based architecture to analyze sequences of SPD matrices without loss of their Riemann…☆38Oct 15, 2024Updated last year
- The PyTorch implementation of "Modeling Financial Time Series using LSTM with Trainable Initial Hidden States"☆11Jul 15, 2020Updated 5 years ago
- PyTorch code of “Out-of-Sample Representation Learning for Multi-Relational Graphs” (EMNLP 2020)☆10Oct 2, 2020Updated 5 years ago
- Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper☆37Jun 11, 2020Updated 6 years ago
- [Pattern Recognition, 2020] Covariance Descriptors on a Gaussian Manifold and their Application to Image Set Classification☆13May 28, 2022Updated 4 years ago
- Code for "Inferring Latent Dynamics Underlying Neural Population Activity via Neural Differential Equations"☆13Jul 26, 2021Updated 4 years ago
- The dataset and codes of the paper UniMod1K: Towards a More Universal Large-Scale Dataset and Benchmark for Multi-Modal Learning.☆17Sep 21, 2025Updated 9 months ago
- Model LEGO: Creating Models Like Disassembling and Assembling Building Blocks☆17Jan 15, 2025Updated last year
- SeRL: Self-Play Reinforcement Learning for Large Language Models with Limited Data☆23Jan 24, 2026Updated 5 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.
- Transformer Doctor: Diagnosing and Treating Vision Transformers☆11Jan 15, 2025Updated last year
- Code for the paper "Refining Language Model with Compositional Explanation" (NeurIPS 2021)☆11Oct 25, 2021Updated 4 years ago
- This is a matlab implementation of our article, titled "DreamNet: A Deep Riemannian Manifold Network for SPD Matrix Learning", which has …☆14Nov 2, 2022Updated 3 years ago
- Understanding the paper "Principles of Riemannian Geometry in Neural Networks" by Michael Hauser and Asok Ray☆11May 24, 2023Updated 3 years ago
- explore the FV3 data for parameterization☆18Jan 7, 2025Updated last year
- 这项目主要收集大规模GNN(图神经网络)的相关研究☆10May 26, 2020Updated 6 years ago
- This is the python implementation of Tensor-CSPNet and Graph-CSPNet.☆86Jan 10, 2026Updated 5 months ago
- [ICML 2019] The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects☆15Apr 12, 2020Updated 6 years ago
- LDS-toolbox: a matlab toolbox for linear dynamical systems (LDSs) modeling☆13Mar 23, 2018Updated 8 years ago
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- ☆11Oct 18, 2022Updated 3 years ago
- Codes of the paper of "Surrogate-Assisted Evolutionary Search of Spiking Neural Architectures in Liquid State Machines"☆12Feb 15, 2023Updated 3 years ago
- Code for the paper 'Geodesic Finite Mixture Model'.☆10Aug 25, 2016Updated 9 years ago
- 🔥MDCS: More Diverse Experts with Consistency Self-distillation for Long-tailed Recognition [Official, ICCV 2023]☆30Oct 26, 2024Updated last year
- Mean-Shift (MS) Mean-Shift (MS) is widely known as one of the most basic yet powerful tracking algorithms. Mean- Shift considers feature …☆11Dec 21, 2017Updated 8 years ago
- Python library to compute functional connectivity measures from EEG☆12Oct 14, 2023Updated 2 years ago
- ☆12Aug 7, 2024Updated last year