Synchronous Generator

Synchronous generators (SGs) are a core component of power systems, and research focuses on improving their modeling and control, particularly in the context of integrating renewable energy sources. Current research employs various machine learning techniques, including recurrent neural networks (RNNs) and deep operator networks (DeepONets), to learn SG dynamics and predict their behavior under diverse conditions, often leveraging data from electromagnetic transient (EMT) simulations. This work is crucial for enhancing power grid stability, reliability, and efficiency, enabling more effective integration of renewable energy and improved fault diagnosis and prediction.

Papers

February 22, 2024

Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfer
Xinshuo Hu, Baotian Hu, Dongfang Li, Xiaoguang Li, Lifeng Shang
General Analysis Context Information Generative Question Synchronous Generator Contextual Knowledge Dynamic Knowledge Context Extrapolation Generative Fidelity

February 15, 2024

Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement
Yuxuan Gu, Yi Jin, Ben Wang, Zhixiang Wei, Xiaoxiao Ma, Pengyang Ling, Haoxuan Wang, Huaian Chen, Enhong Chen
Large Scale Low Light Synchronous Generator Seed Area Retinex Model

January 22, 2024

Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection
Feng Xiong, Thanet Markchom, Ziwei Zheng, Subin Jung, Varun Ojha, Huizhi Liang
Text Classification SemEval 2022 Task Multi Domain Generated Text Synchronous Generator Machine Generated Text

January 15, 2024

The Chronicles of RAG: The Retriever, the Chunk and the Generator
Paulo Finardi, Leonardo Avila, Rodrigo Castaldoni, Pedro Gengo, Celio Larcher, Marcos Piau, Pablo Costa, Vinicius Caridá
Representation Learning Retrieval Augmented Generation Text Generation Retrieval Model Synchronous Generator Chunk Wise Data Diversity Hybrid Retriever

December 5, 2023

Generator Born from Classifier
Runpeng Yu, Xinchao Wang
Gradient Descent Simple Classifier Synchronous Generator Image Generator Image Generation Task Pre Trained Classifier Maximization Bias

December 4, 2023

Training Reinforcement Learning Agents and Humans With Difficulty-Conditioned Generators
Sidney Tio, Jimmy Ho, Pradeep Varakantham
Reinforcement Learning Real Human Reinforcement Learning Agent Synchronous Generator Item Response Theory

November 1, 2023

Optimal Budgeted Rejection Sampling for Generative Models
Alexandre Verine, Muni Sreenivas Pydi, Benjamin Negrevergne, Yann Chevaleyre
Generative Model Generative Modeling Synchronous Generator Sampling Technique Rejection Sampling

October 31, 2023

Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM
Guillermo Alaejos, Adrián Castelló, Pedro Alonso-Jordá, Francisco D. Igual, Héctor Martínez, Enrique S. Quintana-Ortí
Matrix Multiplication Synchronous Generator Single Parent Family Open Source Library High Performance Library Micro Kernel

October 30, 2023

Generator Identification for Linear SDEs with Additive and Multiplicative Noise
Yuanyuan Wang, Xi Geng, Wei Huang, Biwei Huang, Mingming Gong
Causal Inference Synchronous Generator Parameter Identifiability Multiplicative Noise Feed Additive Interventional Distribution

October 10, 2023

Sound-skwatter (Did You Mean: Sound-squatter?) AI-powered Generator for Phishing Prevention
Rodolfo Valentim, Idilio Drago, Marco Mellia, Federico Cerutti
Acoustic Model Synchronous Generator Anti Phishing Social Engineering Attack

July 27, 2023

GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing
Jing Wu, Naira Hovakimyan, Jennifer Hobbs
LeArning Abstract Contrastive Learning Shot Learning Remote Sensing Synchronous Generator Land Cover Classification

July 26, 2023

Learning-based Control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy
Zhenxiao Yin, Xiaobing Dai, Zewen Yang, Yang Shen, Georges Hattab, Hang Zhao
Gaussian Process Learning Based Lyapunov Function Gaussian Process Regression Synchronous Generator Optimal Aggregation

June 22, 2023

Transferable Curricula through Difficulty Conditioned Generators
Sidney Tio, Pradeep Varakantham
Reinforcement Learning Synchronous Generator Difficulty Level Training Robot Curriculum Generation

May 24, 2023

Learning UI-to-Code Reverse Generator Using Visual Critic Without Rendering
Davit Soselia, Khalid Saifullah, Tianyi Zhou
LeArning Abstract Source Code Synchronous Generator Vision Encoders Visual Assessment

May 22, 2023

Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel
Synchronous Generator Counterfactual Data Augmentation Counterfactual Data Counterfactual Augmentation Counterfactual Generative Classifier Robustness

February 27, 2023

Text-only domain adaptation for end-to-end ASR using integrated text-to-mel-spectrogram generator
Vladimir Bataev, Roman Korostik, Evgeny Shabalin, Vitaly Lavrukhin, Boris Ginsburg
End to End Synchronous Generator High Fidelity Vocoder Text Only Domain Adaptation

February 13, 2023

Variational Mixture of HyperGenerators for Learning Distributions Over Functions
Batuhan Koyuncu, Pablo Sanchez-Martin, Ignacio Peis, Pablo M. Olmos, Isabel Valera
Generative Model Variational Autoencoders Synchronous Generator Variational Mixture

January 29, 2023

On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators
Christian Moya, Guang Lin, Tianqiao Zhao, Meng Yue
Average Approximation Response Generation Operator Learning Synchronous Generator Neural Generation Deep Operator DeepONet Framework Power Grid Simulator

December 7, 2022

Optimizing a Digital Twin for Fault Diagnosis in Grid Connected Inverters -- A Bayesian Approach
Pavol Mulinka, Subham Sahoo, Charalampos Kalalas, Pedro H. J. Nardelli
Bayesian Optimization Digital Twin Hyperparameter Tuning Bayesian Approach Synchronous Generator Large Scale Hyperparameter Optimization

November 27, 2022

Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs
Guangrun Wang, Philip H. S. Torr
Adversarial Attack Generative Model Image Generation Supervised ImageNet GAN Model Synchronous Generator Traditional Neural Network

Synchronous Generator

Papers

Does the Generator Mind its Contexts? An Analysis of Generative Model Faithfulness under Context Transfer

Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement

Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection

The Chronicles of RAG: The Retriever, the Chunk and the Generator

Generator Born from Classifier

Training Reinforcement Learning Agents and Humans With Difficulty-Conditioned Generators

Optimal Budgeted Rejection Sampling for Generative Models

Automatic Generators for a Family of Matrix Multiplication Routines with Apache TVM

Generator Identification for Linear SDEs with Additive and Multiplicative Noise

Sound-skwatter (Did You Mean: Sound-squatter?) AI-powered Generator for Phishing Prevention

GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing

Learning-based Control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy

Transferable Curricula through Difficulty Conditioned Generators

Learning UI-to-Code Reverse Generator Using Visual Critic Without Rendering

Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals

Text-only domain adaptation for end-to-end ASR using integrated text-to-mel-spectrogram generator

Variational Mixture of HyperGenerators for Learning Distributions Over Functions

On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators

Optimizing a Digital Twin for Fault Diagnosis in Grid Connected Inverters -- A Bayesian Approach

Traditional Classification Neural Networks are Good Generators: They are Competitive with DDPMs and GANs