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Found 17 papers, 2 papers with code
Revisiting Edge Perturbation for Graph Neural Network in Graph Data Augmentation and Attack
It can be categorized into two veins based on their effects on the performance of graph neural networks (GNNs), i. e., graph data augmentation and attack.
ConUNETR: A Conditional Transformer Network for 3D Micro-CT Embryonic Cartilage Segmentation
Experiments on the mice cartilage dataset show the superiority of our new model compared to other competitive segmentation models.
TLMCM Network for Medical Image Hierarchical Multi-Label Classification
Medical Image Hierarchical Multi-Label Classification (MI-HMC) is of paramount importance in modern healthcare, presenting two significant challenges: data imbalance and \textit{hierarchy constraint}.
Transmission and Distribution Coordination for DER-rich Energy Markets: A Parametric Programming Approach
To compare the proposed framework, an ideal case is defined in which DER aggregators can participate in the wholesale market directly and ISO overseas operation of both transmission and distribution systems.
The FRTB-IMA computational challenge for Equity Autocallables
When the Orthogonal Chebyshev Sliding Technique was introduced it was applied to a portfolio of swaps and swaptions within the context of the FRTB-IMA capital calculation.
Detaching and Boosting: Dual Engine for Scale-Invariant Self-Supervised Monocular Depth Estimation
Monocular depth estimation (MDE) in the self-supervised scenario has emerged as a promising method as it refrains from the requirement of ground truth depth.
EV Charging Station Wholesale Market Participation: A Strategic Bidding and Pricing Approach
In the lower-level problem, the EV owner's utility function is maximized.
Optimal Utilization of Third-Party Demand Response Resources in Vertically Integrated Utilities: A Game Theoretic Approach
The competitions among the EUs in each DR program is captured through a non-cooperative simultaneous game.
ISO and DSO Coordination: A Parametric Programming Approach
In this paper, a framework is proposed to coordinate the operation of the independent system operator (ISO) and distribution system operator (DSO) to leverage the wholesale market participation of distributed energy resources (DERs) aggregators while ensuring secure operation of distribution grids.
A Game Theoretic Approach for Demand Response Allocation among Strategic Prosumers in Regulated Distribution Utilities
A game theoretic model, consisting of a sequential game coupled with a simultaneous game, is proposed to capture the competition and interaction among PV prosumers, the third-party DR providers, and the utility company.
Multi-Critic Actor Learning: Teaching RL Policies to Act with Style
MultiCriticAL is tested in the context of multi-style learning, a special case of MTRL where agents are trained to behave with different distinct behavior styles, and yields up to 45% performance gains over the single-critic baselines and even successfully learns behavior styles in cases where single-critic approaches may simply fail to learn.
Unmasking the Origin of Kinks in the Photoemission Spectra of Cuprate Superconductors
Our results reveal it is the electron density-of-states being the predominant factor in determining the doping-dependence of the kink size, manifesting the multi-band nature of the cuprates, as opposed to the prevalent belief of it being a measure of the mode-coupling strength.
Superconductivity Materials Science
On dimensions of visible parts of self-similar sets with finite rotation groups
The bound is valid for all visible parts and it depends on the penetrable part of the set, which is a concept defined in this paper.
Dynamical Systems Classical Analysis and ODEs 28A80
Real-time Locational Marginal Price Forecasting Using Generative Adversarial Network
In this paper, we propose a model-free unsupervised learning approach to forecast real-time locational marginal prices (RTLMPs) in wholesale electricity markets.
Optimal Participation of Price-maker Battery Energy Storage Systems in Energy and Ancillary Services Markets Considering Degradation Cost
This paper proposes a bi-level optimization framework to investigate the optimal market operation strategies of price-maker battery energy storage systems (BESSs) in real-time energy, spinning reserve, and pay as performance regulation markets, with a special focus on understanding BESS's excessive regulation market participation observed by several system operators and the impact of battery degradation cost on BESS market activities.
Predicting Real-Time Locational Marginal Prices: A GAN-Based Video Prediction Approach
In this paper, we propose an unsupervised data-driven approach to predict real-time locational marginal prices (RTLMPs).
ENCASE: An ENsemble ClASsifiEr for ECG classification using expert features and deep neural networks
We propose ENCASE to combine expert features and DNNs (Deep Neural Networks) together for ECG classification.
Ranked #1 on
Time Series Classification
on Physionet 2017 Atrial Fibrillation
(F1 (Hidden Test Set) metric)
