Summary of Solving Nonlinear Energy Supply and Demand System Using Physics-informed Neural Networks, by Van Truong Vo et al.
Solving Nonlinear Energy Supply and Demand System Using Physics-Informed Neural Networksby Van Truong Vo, Samad…
Solving Nonlinear Energy Supply and Demand System Using Physics-Informed Neural Networksby Van Truong Vo, Samad…
HyperNet Fields: Efficiently Training Hypernetworks without Ground Truth by Learning Weight Trajectoriesby Eric Hedlin, Munawar…
Data value estimation on private gradientsby Zijian Zhou, Xinyi Xu, Daniela Rus, Bryan Kian Hsiang…
A Meta-Learning Approach to Bayesian Causal Discoveryby Anish Dhir, Matthew Ashman, James Requeima, Mark van…
Breaking the Context Bottleneck on Long Time Series Forecastingby Chao Ma, Yikai Hou, Xiang Li,…
FedGA: Federated Learning with Gradient Alignment for Error Asymmetry Mitigationby Chenguang Xiao, Zheming Zuo, Shuo…
Topology-Aware 3D Gaussian Splatting: Leveraging Persistent Homology for Optimized Structural Integrityby Tianqi Shen, Shaohua Liu,…
Deep Learning for Spatio-Temporal Fusion in Land Surface Temperature Estimation: A Comprehensive Survey, Experimental Analysis,…
Transformer-based toxin-protein interaction analysis prioritizes airborne particulate matter components with potential adverse health effectsby Yan…
Subgoal Discovery Using a Free Energy Paradigm and State Aggregationsby Amirhossein Mesbah, Reshad Hosseini, Seyed…