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Found 7 papers, 1 papers with code
Temporal-Spatial Object Relations Modeling for Vision-and-Language Navigation
To avoid this problem, we construct object connections based on observations from all viewpoints in the navigational environment, which ensures complete spatial coverage and eliminates the gap, called Spatial Object Relations (SOR).
CPCL: Cross-Modal Prototypical Contrastive Learning for Weakly Supervised Text-based Person Re-Identification
Weakly supervised text-based person re-identification (TPRe-ID) seeks to retrieve images of a target person using textual descriptions, without relying on identity annotations and is more challenging and practical.
Enhancing Building Energy Efficiency through Advanced Sizing and Dispatch Methods for Energy Storage
The solution is determined considering both capital costs in optimal sizing and operational benefits in optimal dispatch.
Policy Learning based on Deep Koopman Representation
This paper proposes a policy learning algorithm based on the Koopman operator theory and policy gradient approach, which seeks to approximate an unknown dynamical system and search for optimal policy simultaneously, using the observations gathered through interaction with the environment.
Deep Koopman Learning of Nonlinear Time-Varying Systems
This paper presents a data-driven approach to approximate the dynamics of a nonlinear time-varying system (NTVS) by a linear time-varying system (LTVS), which is resulted from the Koopman operator and deep neural networks.
CSMCNet: Scalable Video Compressive Sensing Reconstruction with Interpretable Motion Estimation
Most deep network methods for compressive sensing reconstruction suffer from the black-box characteristic of DNN.
A Convex Approach to Data-driven Optimal Control via Perron-Frobenius and Koopman Operators
We provide a convex formulation for the optimal control problem of the nonlinear system.
Optimization and Control Systems and Control Systems and Control Dynamical Systems
