Results 211 to 220 of about 34,520,301 (258)

Mamba-360: Survey of State Space Models as Transformer Alternative for Long Sequence Modelling: Methods, Applications, and Challenges

arXiv.org
Sequence modeling is a crucial area across various domains, including Natural Language Processing (NLP), speech recognition, time series forecasting, music generation, and bioinformatics.
B. Patro, V. Agneeswaran
semanticscholar   +1 more source

MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection

Neural Information Processing Systems
Recent advancements in anomaly detection have seen the efficacy of CNN- and transformer-based approaches. However, CNNs struggle with long-range dependencies, while transformers are burdened by quadratic computational complexity. Mamba-based models, with
Hao-Yang He, Yuhu Bai, Jiang-Ning Zhang, Qingdong He, Hongxu Chen, Z. Gan, Chengjie Wang, Xiang-Tai Li, Guan-Zhong Tian, Lei Xie   +9 more
semanticscholar   +1 more source

Point Cloud Mamba: Point Cloud Learning via State Space Model

AAAI Conference on Artificial Intelligence
Recently, state space models have exhibited strong global modeling capabilities and linear computational complexity in contrast to transformers. This research focuses on applying such architecture to more efficiently and effectively model point cloud ...
Tao Zhang, Haobo Yuan, Lu Qi, Jiang-Ning Zhang, Qian-Yu Zhou, Shun-Ping Ji, Shui-Cheng Yan, Xiang-Tai Li   +7 more
semanticscholar   +1 more source

Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection

Neural Information Processing Systems
Serialization-based methods, which serialize the 3D voxels and group them into multiple sequences before inputting to Transformers, have demonstrated their effectiveness in 3D object detection.
Guowen Zhang, Lue Fan, Chen-Hang He, Zhen Lei, Zhaoxiang Zhang, Lei Zhang   +5 more
semanticscholar   +1 more source

Point Mamba: A Novel Point Cloud Backbone Based on State Space Model with Octree-Based Ordering Strategy

arXiv.org
Recently, state space model (SSM) has gained great attention due to its promising performance, linear complexity, and long sequence modeling ability in both language and image domains.
Jiu-Ming Liu, Rui Yu, Yian Wang, Yu Zheng, Tianchen Deng, Weicai Ye, He-Sheng Wang   +6 more
semanticscholar   +1 more source