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Found 9 papers, 3 papers with code
Weak Collocation Regression method: fast reveal hidden stochastic dynamics from high-dimensional aggregate data
Taking the collocations of Gaussian functions as the test functions in the weak form of the FP equation, we transfer the derivatives to the Gaussian functions and thus approximate the weak form by the expectational sum of the data.
On the Performance of Data Compression in Clustered Fog Radio Access Networks
The fog-radio-access-network (F-RAN) has been proposed to address the strict latency requirements, which offloads computation tasks generated in user equipments (UEs) to the edge to reduce the processing latency.
Few-Shot Stance Detection via Target-Aware Prompt Distillation
The main challenge of this task comes two-fold: few-shot learning resulting from the varying targets and the lack of contextual information of the targets.
Structured Neural-PI Control for Networked Systems: Stability and Steady-State Optimality Guarantees
We explicitly characterize the stability conditions and engineer neural networks that satisfy them by design.
Stable Reinforcement Learning for Optimal Frequency Control: A Distributed Averaging-Based Integral Approach
Specifically, we use RL to learn a neural network-based control policy mapping from the integral variables of DAI to the controllable power injections which provides optimal transient frequency control, while DAI inherently ensures the frequency restoration and optimal economic dispatch.
Modified Gaussian Process Regression Models for Cyclic Capacity Prediction of Lithium-ion Batteries
Experimental results demonstrate that the modified Gaussian process regression model considering the battery electrochemical and empirical ageing signature outperforms other counterparts and is able to achieve satisfactory results for both one-step and multi-step predictions.
Reinforcement Learning for Optimal Primary Frequency Control: A Lyapunov Approach
As more inverter-connected renewable resources are integrated into the grid, frequency stability may degrade because of the reduction in mechanical inertia and damping.
An adaptive high-order piecewise polynomial based sparse grid collocation method with applications
The contribution of this work is the introduction of a systematic framework for collocation onto high-order piecewise polynomial space that is allowed to be discontinuous.
Numerical Analysis Numerical Analysis
Algorithms for Generalized Cluster-wise Linear Regression
We examine the performance of our algorithms on a stock keeping unit (SKU) clustering problem employed in forecasting halo and cannibalization effects in promotions using real-world retail data from a large supermarket chain.
