Research graph
References from Financial fraud risk prediction using a CNN-Mamba-Transformer model. Local targets link to admitted publications; unresolved targets remain external evidence.
Using machine learning Meta-Classifiers to detect financial frauds
10.1016/j.frl.2022.102915 · 2022 · External reference
Detecting financial statement fraud using dynamic ensemble machine learning
10.1016/j.irfa.2023.102827 · 2023 · External reference
Improving prediction of cervical cancer using KNN imputer and multi-model ensemble learning
10.1371/journal.pone.0295632 · 2024 · External reference
Audit committee financial expertise and earnings management: The role of status
10.1016/j.jacceco.2014.08.006 · 2014 · External reference
Detecting accounting fraud in publicly traded U.S. firms using a machine learning approach
10.1111/1475-679x.12292 · 2020 · External reference
Detecting GAAP violation: Implications for assessing earnings management among firms with extreme financial performance
10.1016/s0278-4254(97)00023-9 · 1997 · External reference
The detection of earnings manipulation
10.2469/faj.v55.n5.2296 · 1999 · External reference
Using nonfinancial measures to assess fraud risk
10.1111/j.1475-679x.2009.00349.x · 2009 · External reference
Detecting management fraud in public companies
10.1287/mnsc.1100.1174 · 2010 · External reference
Jump detection using deep learning: With applications to financial time series data
10.1007/s10614-025-10949-6 · 2026 · External reference
Financial fraud detection of listed companies in China: A machine learning approach
2023 · External reference
Corporate fraud and bank loans: Evidence from China
10.1016/j.cjar.2011.07.001 · 2011 · External reference
Reducing overfitting in deep networks by decorrelating representations
2015 · External reference
Bank complexity, governance, and risk
10.1016/j.jbankfin.2020.106013 · 2022 · External reference
Predicting material accounting misstatements
10.1111/j.1911-3846.2010.01041.x · 2011 · External reference
Internal control weaknesses and financial reporting fraud
10.2308/ajpt-51608 · 2017 · External reference
Who blows the whistle on corporate fraud?
10.1111/j.1540-6261.2010.01614.x · 2010 · External reference
Cooking the books: Recipes and costs of falsified financial statements in China
10.1016/j.jcorpfin.2010.09.002 · 2011 · External reference
Who cares about corporate fraud? Evidence from cross-border mergers and acquisitions of Chinese companies
10.1007/s11156-022-01111-6 · 2023 · External reference
Supporting analysis of dimensionality reduction results with contrastive learning
10.1109/tvcg.2019.2934251 · 2020 · External reference
Evasive shareholder meetings and corporate fraud
10.1016/j.jcorpfin.2020.101807 · 2021 · External reference
Transformer networks for trajectory forecasting
2021 · External reference
RiskMamba: A lightweight and efficient model for enterprise financial risk prediction with multi-scale temporal modeling
10.4018/joeuc.390235 · 2025 · External reference
Predicting bulge to total luminosity ratio of galaxies using deep learning
10.1093/mnras/stab1935 · 2021 · External reference
Mamba: Linear-time sequence modeling with selective state spaces
2024 · External reference
An efficient and mixed heterogeneous model for image restoration
2025 · External reference
Convolutional neural network learning for generic data classification
10.1016/j.ins.2018.10.053 · 2019 · External reference
Equity incentives and corporate fraud in China
10.1007/s10551-015-2774-2 · 2016 · External reference
Does CSR engagement deter corporate misconduct? Quasi-natural experimental evidence from firms joining a government-initiated social program in China
10.1007/s10551-023-05589-5 · 2024 · External reference
Learning from imbalanced data
10.1109/tkde.2008.239 · 2009 · External reference
Corporate governance in China: A modern perspective
10.1016/j.jcorpfin.2014.10.010 · 2015 · External reference
Corporate governance in China: A survey
10.1093/rof/rfaa012 · 2020 · External reference
Reputation concerns of independent directors: Evidence from individual director voting
2016 · External reference
CINFormer: Transformer network with multi-stage CNN feature injection for surface defect segmentation
2023 · External reference
The analysis of fraud detection in financial market under machine learning
2025 · External reference
Machine learning: Trends, perspectives, and prospects
10.1126/science.aaa8415 · 2015 · External reference
Prediction policy problems
10.1257/aer.p20151023 · 2015 · External reference
The supply of corporate directors and board independence
10.1093/rfs/hht020 · 2013 · External reference
Corporate governance, fraud learning cycles, and financial fraud detection: Evidence from Chinese listed firms
10.1016/j.ribaf.2025.102832 · 2025 · External reference
A survey of convolutional neural networks: Analysis, applications, and prospects
10.1109/tnnls.2021.3084827 · 2022 · External reference
Shangshi gongsi caiwu wubi shibie moxing sheji ji qi yingyong yanjiu: Jiyu xinxing jiqi xuexi suanfa [Design and application of a financial fraud detection model for listed companies: Based on emerging machine learning algorithms]
2022 · External reference
A unified approach to interpreting model predictions
2017 · External reference
Financial reporting fraud detection: An analysis of data mining algorithms
2020 · External reference
Machine learning with oversampling and undersampling techniques: Overview study and experimental results
2020 · External reference
A SMOTe based oversampling data-point approach to solving the credit card data imbalance problem in financial fraud detection
10.12785/ijcds/100128 · 2021 · External reference
Using a novel ensemble learning framework to detect financial reporting misconduct
10.1080/23270012.2023.2258372 · 2023 · External reference
From classroom to boardroom: The value of academic independent directors in China
10.1016/j.pacfin.2020.101319 · 2020 · External reference
Financial statement fraud detection: An analysis of statistical and machine learning algorithms
10.2308/ajpt-50009 · 2011 · External reference
A one-dimensional convolutional neural network (1D-CNN) based deep learning system for network intrusion detection
10.3390/app12167986 · 2022 · External reference
Soft reordering one-dimensional convolutional neural network for credit scoring
10.1016/j.knosys.2023.110414 · 2023 · External reference
Detection of financial statement fraud and feature selection using data mining techniques
10.1016/j.dss.2010.11.006 · 2011 · External reference
Causes, consequences, and deterence of financial statement fraud
10.1016/s1045-2354(03)00072-8 · 2005 · External reference
Disclosure tone and shareholder litigation
10.2308/accr-10137 · 2011 · External reference
Financial time series forecasting with deep learning: A systematic literature review: 2005–2019
10.1016/j.asoc.2020.106181 · 2020 · External reference
Unsupervised learning for financial statement fraud detection using manta ray foraging based convolutional neural network
10.1002/cpe.7340 · 2022 · External reference
Do site visits mitigate corporate fraudulence? Evidence from China
10.1016/j.irfa.2021.101940 · 2021 · External reference
Duli dongshi kunbang pinren yu yingyu guanli: “Gangzheng bu'e” haishi “Anfen shouji” [Bundled appointments of independent directors and earnings management: Uncompromising integrity or passive compliance?]
2025 · External reference
Fraudulently misstated financial statements and insider trading: An empirical analysis
10.2308/tar-274320 · 1998 · External reference
Digital finance and corporate financial fraud
10.1016/j.irfa.2023.102566 · 2023 · External reference
Jiyu Benford lü de suiji senlin moxing ji qi zai caiwu fengxian yujing de yingyong [A random forest model based on Benford's law and its application to financial risk early warning]
2021 · External reference
Gated recurrent unit network: A promising approach to corporate default prediction
10.1002/for.3057 · 2024 · External reference
Attention is all you need
2017 · External reference
Does audit quality affect firm innovation?
2024 · External reference
Financial statement fraud, recidivism and punishment
10.1016/j.ememar.2023.101033 · 2023 · External reference
Financial literacy and fraud detection——Evidence from China
10.1016/j.iref.2021.06.017 · 2021 · External reference
Watchdog from academia: Do academic independent directors matter for financial statement fraud?
10.1016/j.iref.2025.104219 · 2025 · External reference
Financial distress prediction using integrated Z-score and multilayer perceptron neural networks
10.1016/j.dss.2022.113814 · 2022 · External reference
Enhanced detection of accounting fraud using a CNN-LSTM-Attention model optimized by Sparrow search
10.7717/peerj-cs.2532 · 2024 · External reference
Institutional investors, political connections, and the incidence of regulatory enforcement against corporate fraud
10.1007/s10551-014-2392-4 · 2016 · External reference
Fault diagnosis of motor bearing in complex scenarios based on Mamba and Indicative Contrastive Learning
10.1016/j.engappai.2025.110216 · 2025 · External reference
Board age and corporate financial fraud: An interactionist view
10.1016/j.lrp.2017.08.001 · 2018 · External reference
The determinants of financial fraud in Chinese firms: Does corporate governance as an institutional innovation matter?
10.1016/j.techfore.2017.06.035 · 2017 · External reference
Detecting financial fraud in listed companies via a CNN-Transformer framework
2025 · External reference
Separation and concentration in deep networks
2020 · External reference
Shuju zichan xinxi pilu dui kehu wendingxing de yingxiang yanjiu [Research on the impact of data asset information disclosure on customer stability]
2025 · External reference
HA-Tracker: A hybrid architecture tracker with spatiotemporal Mamba motion model for UAV-based video multi-object tracking
10.3390/rs18010133 · 2026 · External reference
Jiyu XGBoost de shangshi gongsi caiwu wubi yuce moxing yanjiu [An XGBoost-based model for predicting financial fraud in listed companies]
2022 · External reference
Using data-driven methods to detect financial statement fraud in the real scenario
10.1016/j.accinf.2024.100693 · 2024 · External reference
Accounting fraud detection through textual risk disclosures in annual reports: From the perspective of SEC guidelines
10.1111/acfi.13390 · 2025 · External reference
Unsupervised learning for financial statement fraud detection using manta ray foraging based convolutional neural network
10.1002/cpe.7340 · ExternalCitation · doi-reference
Gated recurrent unit network: A promising approach to corporate default prediction
10.1002/for.3057 · ExternalCitation · doi-reference
Institutional investors, political connections, and the incidence of regulatory enforcement against corporate fraud
10.1007/s10551-014-2392-4 · ExternalCitation · doi-reference
Equity incentives and corporate fraud in China
10.1007/s10551-015-2774-2 · ExternalCitation · doi-reference
Does CSR engagement deter corporate misconduct? Quasi-natural experimental evidence from firms joining a government-initiated social program in China
10.1007/s10551-023-05589-5 · ExternalCitation · doi-reference
Jump detection using deep learning: With applications to financial time series data
10.1007/s10614-025-10949-6 · ExternalCitation · doi-reference
Who cares about corporate fraud? Evidence from cross-border mergers and acquisitions of Chinese companies
10.1007/s11156-022-01111-6 · ExternalCitation · doi-reference
Using data-driven methods to detect financial statement fraud in the real scenario
10.1016/j.accinf.2024.100693 · ExternalCitation · doi-reference
Financial time series forecasting with deep learning: A systematic literature review: 2005–2019
10.1016/j.asoc.2020.106181 · ExternalCitation · doi-reference
Corporate fraud and bank loans: Evidence from China
10.1016/j.cjar.2011.07.001 · ExternalCitation · doi-reference
Detection of financial statement fraud and feature selection using data mining techniques
10.1016/j.dss.2010.11.006 · ExternalCitation · doi-reference
Financial distress prediction using integrated Z-score and multilayer perceptron neural networks
10.1016/j.dss.2022.113814 · ExternalCitation · doi-reference
Financial statement fraud, recidivism and punishment
10.1016/j.ememar.2023.101033 · ExternalCitation · doi-reference
Fault diagnosis of motor bearing in complex scenarios based on Mamba and Indicative Contrastive Learning
10.1016/j.engappai.2025.110216 · ExternalCitation · doi-reference
Using machine learning Meta-Classifiers to detect financial frauds
10.1016/j.frl.2022.102915 · ExternalCitation · doi-reference
Convolutional neural network learning for generic data classification
10.1016/j.ins.2018.10.053 · ExternalCitation · doi-reference
Financial literacy and fraud detection——Evidence from China
10.1016/j.iref.2021.06.017 · ExternalCitation · doi-reference
Watchdog from academia: Do academic independent directors matter for financial statement fraud?
10.1016/j.iref.2025.104219 · ExternalCitation · doi-reference
Do site visits mitigate corporate fraudulence? Evidence from China
10.1016/j.irfa.2021.101940 · ExternalCitation · doi-reference
Digital finance and corporate financial fraud
10.1016/j.irfa.2023.102566 · ExternalCitation · doi-reference
Detecting financial statement fraud using dynamic ensemble machine learning
10.1016/j.irfa.2023.102827 · ExternalCitation · doi-reference
Audit committee financial expertise and earnings management: The role of status
10.1016/j.jacceco.2014.08.006 · ExternalCitation · doi-reference
Bank complexity, governance, and risk
10.1016/j.jbankfin.2020.106013 · ExternalCitation · doi-reference
Cooking the books: Recipes and costs of falsified financial statements in China
10.1016/j.jcorpfin.2010.09.002 · ExternalCitation · doi-reference
Corporate governance in China: A modern perspective
10.1016/j.jcorpfin.2014.10.010 · ExternalCitation · doi-reference
Evasive shareholder meetings and corporate fraud
10.1016/j.jcorpfin.2020.101807 · ExternalCitation · doi-reference
Soft reordering one-dimensional convolutional neural network for credit scoring
10.1016/j.knosys.2023.110414 · ExternalCitation · doi-reference
Board age and corporate financial fraud: An interactionist view
10.1016/j.lrp.2017.08.001 · ExternalCitation · doi-reference
From classroom to boardroom: The value of academic independent directors in China
10.1016/j.pacfin.2020.101319 · ExternalCitation · doi-reference
Corporate governance, fraud learning cycles, and financial fraud detection: Evidence from Chinese listed firms
10.1016/j.ribaf.2025.102832 · ExternalCitation · doi-reference
The determinants of financial fraud in Chinese firms: Does corporate governance as an institutional innovation matter?
10.1016/j.techfore.2017.06.035 · ExternalCitation · doi-reference
Detecting GAAP violation: Implications for assessing earnings management among firms with extreme financial performance
10.1016/s0278-4254(97)00023-9 · ExternalCitation · doi-reference
Causes, consequences, and deterence of financial statement fraud
10.1016/s1045-2354(03)00072-8 · ExternalCitation · doi-reference
Using a novel ensemble learning framework to detect financial reporting misconduct
10.1080/23270012.2023.2258372 · ExternalCitation · doi-reference
Predicting bulge to total luminosity ratio of galaxies using deep learning
10.1093/mnras/stab1935 · ExternalCitation · doi-reference
The supply of corporate directors and board independence
10.1093/rfs/hht020 · ExternalCitation · doi-reference
Corporate governance in China: A survey
10.1093/rof/rfaa012 · ExternalCitation · doi-reference
Learning from imbalanced data
10.1109/tkde.2008.239 · ExternalCitation · doi-reference
A survey of convolutional neural networks: Analysis, applications, and prospects
10.1109/tnnls.2021.3084827 · ExternalCitation · doi-reference
Supporting analysis of dimensionality reduction results with contrastive learning
10.1109/tvcg.2019.2934251 · ExternalCitation · doi-reference
Detecting accounting fraud in publicly traded U.S. firms using a machine learning approach
10.1111/1475-679x.12292 · ExternalCitation · doi-reference
Accounting fraud detection through textual risk disclosures in annual reports: From the perspective of SEC guidelines
10.1111/acfi.13390 · ExternalCitation · doi-reference
Using nonfinancial measures to assess fraud risk
10.1111/j.1475-679x.2009.00349.x · ExternalCitation · doi-reference
Who blows the whistle on corporate fraud?
10.1111/j.1540-6261.2010.01614.x · ExternalCitation · doi-reference
Predicting material accounting misstatements
10.1111/j.1911-3846.2010.01041.x · ExternalCitation · doi-reference
Machine learning: Trends, perspectives, and prospects
10.1126/science.aaa8415 · ExternalCitation · doi-reference
Prediction policy problems
10.1257/aer.p20151023 · ExternalCitation · doi-reference
A SMOTe based oversampling data-point approach to solving the credit card data imbalance problem in financial fraud detection
10.12785/ijcds/100128 · ExternalCitation · doi-reference
Detecting management fraud in public companies
10.1287/mnsc.1100.1174 · ExternalCitation · doi-reference
Improving prediction of cervical cancer using KNN imputer and multi-model ensemble learning
10.1371/journal.pone.0295632 · ExternalCitation · doi-reference
Disclosure tone and shareholder litigation
10.2308/accr-10137 · ExternalCitation · doi-reference
Financial statement fraud detection: An analysis of statistical and machine learning algorithms
10.2308/ajpt-50009 · ExternalCitation · doi-reference
Internal control weaknesses and financial reporting fraud
10.2308/ajpt-51608 · ExternalCitation · doi-reference
Fraudulently misstated financial statements and insider trading: An empirical analysis
10.2308/tar-274320 · ExternalCitation · doi-reference
The detection of earnings manipulation
10.2469/faj.v55.n5.2296 · ExternalCitation · doi-reference
A one-dimensional convolutional neural network (1D-CNN) based deep learning system for network intrusion detection
10.3390/app12167986 · ExternalCitation · doi-reference
HA-Tracker: A hybrid architecture tracker with spatiotemporal Mamba motion model for UAV-based video multi-object tracking
10.3390/rs18010133 · ExternalCitation · doi-reference
RiskMamba: A lightweight and efficient model for enterprise financial risk prediction with multi-scale temporal modeling
10.4018/joeuc.390235 · ExternalCitation · doi-reference
Enhanced detection of accounting fraud using a CNN-LSTM-Attention model optimized by Sparrow search
10.7717/peerj-cs.2532 · ExternalCitation · doi-reference
