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Found 10 papers, 5 papers with code
Flexibility Pricing in Distribution Systems: A Direct Method Aligned with Flexibility Models
We then propose a flexibility cost formulation aligned with the aggregated flexibility model and design a DSO flexibility market model to activate the aggregated flexibility in the distribution system to participate in the transmission system operation for energy arbitrage and ancillary services provision.
Generative Hierarchical Temporal Transformer for Hand Action Recognition and Motion Prediction
We present a novel framework that concurrently tackles hand action recognition and 3D future hand motion prediction.
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
Large language models (LLMs) have achieved remarkable performance in natural language understanding and generation tasks.
Improved Inner Approximation for Aggregating Power Flexibility in Active Distribution Networks and its Applications
Concise and reliable modeling for aggregating power flexibility of distributed energy resources in active distribution networks (ADNs) is a crucial technique for coordinating transmission and distribution networks.
IMKGA-SM: Interpretable Multimodal Knowledge Graph Answer Prediction via Sequence Modeling
Then, the knowledge graph link prediction task is modelled as an offline reinforcement learning Markov decision model, which is then abstracted into a unified sequence framework.
Hierarchical Temporal Transformer for 3D Hand Pose Estimation and Action Recognition from Egocentric RGB Videos
Understanding dynamic hand motions and actions from egocentric RGB videos is a fundamental yet challenging task due to self-occlusion and ambiguity.
Gen6D: Generalizable Model-Free 6-DoF Object Pose Estimation from RGB Images
In this paper, we present a generalizable model-free 6-DoF object pose estimator called Gen6D.
Aggregated Feasible Region of Heterogeneous Demand-Side Flexible Resources---Part I: Theoretical Derivation of the Exact Model
The number of constraints is linear with the number of resources and is exponential with the number of time intervals, respectively.
Data-Driven Scheduling of Electric Boiler with Thermal Storage for Providing Power Balancing Service
Through the case study, it is found that the proposed method can save the total operation cost of the EBTS compared with the deterministic EBTS operation optimization model.
DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose Estimation
Scalable 6D pose estimation for rigid objects from RGB images aims at handling multiple objects and generalizing to novel objects.
