A5041402055- Mechatronics Education and Applications
- E-commerce and Technology Innovations
- Advanced Data Compression Techniques
- Complex Network Analysis Techniques
- Biomedical and Engineering Education
- Customer churn and segmentation
- Computer Graphics and Visualization Techniques
- Advanced Vision and Imaging
- Complex Systems and Time Series Analysis
- Text and Document Classification Technologies
- Data Mining Algorithms and Applications
- Market Dynamics and Volatility
- Insurance and Financial Risk Management
- Human Pose and Action Recognition
- Chronic Lymphocytic Leukemia Research
- 3D Shape Modeling and Analysis
- Immunodeficiency and Autoimmune Disorders
- Video Coding and Compression Technologies
- Domain Adaptation and Few-Shot Learning
- Internet Traffic Analysis and Secure E-voting
Jiangsu Vocational College of Medicine
2025
Toyota Research Institute
2024
Institute of Electrical and Electronics Engineers
2021-2023
University of Toronto
2021-2022
Mount Royal University
2021-2022
Nanyang Technological University
2021-2022
Purdue University System
2021-2022
University of Limerick
2021-2022
Hong Kong Baptist University
2021
University of Canberra
2021
Recent advances in deep learning and large language models (LLMs) have facilitated the deployment of mixture-of-experts (MoE) mechanism stock investment domain. While these demonstrated promising trading performance, they are often unimodal, neglecting wealth information available other modalities, such as textual data. Moreover, traditional neural network-based router selection fails to consider contextual real-world nuances, resulting suboptimal expert selection. To address limitations, we...
Abstract Macroeconomic changes will impact financial market stability through certain pathways. This paper uses big data technology to analyze relevant research literature and determine the evaluation index of macroeconomic index. The GARCH model is used quantitatively measure as an independent variable in empirical analysis. measured by system, indexes that contribute more system are explored principal components using component vector autoregressive based on Lag 2 empirically analyzes...
The common trade-offs of state-of-the-art methods for multi-shape representation (a single model "packing" multiple objects) involve trading modeling accuracy against memory and storage. We show how to encode shapes represented as continuous neural fields with a higher degree precision than previously possible low usage. Key our approach is recursive hierarchical formulation that exploits object self-similarity, leading highly compressed efficient shape latent space. Thanks the formulation,...
Large-scale visuomotor policy learning is a promising approach toward developing generalizable manipulation systems. Yet, policies that can be deployed on diverse embodiments, environments, and observational modalities remain elusive. In this work, we investigate how knowledge from large-scale visual data of the world may used to address one axis variation for manipulation: viewpoint. Specifically, study single-image novel view synthesis models, which learn 3D-aware scene-level priors by...
Under the new quality productivity perspective, artificial intelligence (AI) visual technology provides opportunities for innovation and inheritance of non-heritage culture. The Grass Dragon Lizhuang, as a unique cultural treasure Lizhuang Town, Cuiping District, Yibin City, not only carries profound historical heritage, but also shows traditional wisdom creativity Chinese nation with its art form production process. In this paper, we will take dance City an example to explore how use AI...