Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Alias-Free Mamba Neural Operator
Authors: Jianwei Zheng, Wei Li, Ni Xu, Junwei Zhu, XiaoxuLin , Xiaoqin Zhang
NeurIPS 2024 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Mamba NOs are evaluated on a diverse set of benchmarks with possibly multi-scale solutions and set new state-of-the-art scores, yet with fewer parameters and better efficiency. |
| Researcher Affiliation | Academia | Jianwei Zheng, Wei Li, Ni Xu, Junwei Zhu, Xiaoxu Lin, and Xiaoqin Zhang Zhejiang University of Technology, Hangzhou, Zhejiang |
| Pseudocode | Yes | Algorithm 1 SSM Block (Mamba Integration) |
| Open Source Code | Yes | Codes are available 2. https://github.com/ZhengJianwei2/Mamba-Neural-Operator. |
| Open Datasets | Yes | Representative PDE Benchmarks (RPB). As a standard set of benchmarks for machine learning of PDEs, RBP focuses solely on two-dimensional PDEs... on a larger dataset[33] (10,000 samples, with 7,000 used for training) |
| Dataset Splits | Yes | For the training phase, we produce 1024 samples, and for the evaluation phase, we furnish 256 samples each for both in-distribution and out-of-distribution testing... A validation set, composed of 128 samples, is also constructed for model selection purpose. |
| Hardware Specification | Yes | For fairness and reliability, all experiments are consistently conducted on standardized platform with an NVIDIA RTX 3090 GPU and 2.40GHz Intel(R) Xeon(R) Silver 4210R CPU. |
| Software Dependencies | No | The paper mentions general deep learning frameworks and tools but does not provide specific version numbers for software dependencies such as PyTorch, TensorFlow, CUDA, or other libraries. |
| Experiment Setup | Yes | Training Details and Baselines. For fairness and reliability, all experiments are consistently conducted on standardized platform... Table 8: Mamba NO best-performing hyperparameters configuration for different benchmarks. η, γ, and ω represent the learning rate, scheduler gamma, and weight decay, respectively. Convolution Integration and Mamba Integration denote the quantities of each in a single layer of kernel integration. |