Matrix Manifold Neural Networks++
Authors: Xuan Son Nguyen, Shuo Yang, Aymeric Histace
ICLR 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the effectiveness of the proposed approach in the human action recognition and node classification tasks. |
| Researcher Affiliation | Academia | Xuan Son Nguyen, Shuo Yang, Aymeric Histace ETIS, UMR 8051, CY Cergy Paris University, ENSEA, CNRS, France {xuan-son.nguyen,shuo.yang,aymeric.histace}@ensea.fr |
| Pseudocode | Yes | Algorithm 1: Computation of Pseudo-gyrodistances |
| Open Source Code | No | The paper does not provide an explicit statement about releasing source code or a direct link to a code repository for its methodology. |
| Open Datasets | Yes | We use three datasets, i.e., HDM05 (M uller et al., 2007), FPHA (Garcia-Hernando et al., 2018), and NTU RBG+D 60 (NTU60) (Shahroudy et al., 2016). |
| Dataset Splits | Yes | We use the 70/15/15 percent splits (Chami et al., 2019) for Airport dataset, and standard splits in GCN Kipf & Welling (2017) for Pubmed and Cora datasets. |
| Hardware Specification | Yes | Experiments are conducted on a machine with Intel Core i7-8565U CPU 1.80 GHz 24GB RAM. |
| Software Dependencies | No | The paper mentions using "Py Torch framework" but does not specify a version number for PyTorch or any other software dependencies. |
| Experiment Setup | Yes | These networks are trained using cross-entropy loss and Adadelta optimizer for 2000 epochs. The learning rate is set to 10 3. The factors β (see Proposition 3.4) and λ (see Definition 3.9) are set to 0 and 1, respectively. ... We use a batch size of 32 for HDM05 and FPHA datasets, and a batch size of 256 for NTU60 dataset. |