Statistical Protection for Statistical Databases. - Henri Luchian; Daniel Stamate (SSDBM, 1992)

A User-Oriented Approach for the Protection of Statistical Databases. - Henri Luchian; Daniel Stamate (Sci. Ann. Cuza Univ., 1992)

A General Model for the Answer-Perturbation Techniques. - Daniel Stamate; Henri Luchian; Ben Paechter (SSDBM, 1994)

Bases de données avec informations incertaines. Sémantique et mises à jour. - Nicolas Spyratos; Daniel Stamate (JFPLC, 1996)

Semantics and Containment with Internal and External Conjunctions. - Gösta Grahne; Nicolas Spyratos; Daniel Stamate (ICDT, 1997)

Unification des sémantiques usuelles de programmes logiques. - Yann Loyer; Nicolas Spyratos; Daniel Stamate (JFPLC, 1998)

Computing and Comparing Semantics of Programs in Four-Valued Logics. - Yann Loyer; Nicolas Spyratos; Daniel Stamate (MFCS, 1999)

Hypothesis Support for Information Integration in Four-Valued Logics. - Yann Loyer; Nicolas Spyratos; Daniel Stamate (IFIP TCS, 2000)

Integration of Information in Four-Valued Logics under Non-Uniform Assumptions. - Yann Loyer; Nicolas Spyratos; Daniel Stamate (ISMVL, 2000)

Test d'hypothèses pour l'intégration d'information en logique à quatre valeurs. - Yann Loyer; Nicolas Spyratos; Daniel Stamate (JFPLC, 2000)

Computing and Comparing Semantics of Programs in Multi-valued Logics - Yann Loyer; Nicolas Spyratos; Daniel Stamate (CoRR, 2000)

Hypotheses Founded Semantics of Logic Programs for Information Integration in Multi-Valued Logics - Yann Loyer; Nicolas Spyratos; Daniel Stamate (CoRR, 2001)

Parametrized semantics of logic programs–a unifying framework. - Yann Loyer; Nicolas Spyratos; Daniel Stamate (Theor. Comput. Sci., 2003)

Hypothesis-based semantics of logic programs in multivalued logics. - Yann Loyer; Nicolas Spyratos; Daniel Stamate (ACM Trans. Comput. Log., 2004)

Assumption based multi-valued semantics for extended logic programs. - Daniel Stamate (ISMVL, 2006)

Reduction in Dimensions and Clustering Using Risk and Return Model. - Sayed W. Qaiyumi; Daniel Stamate (AINA Workshops (1), 2007)

Default Reasoning with Imperfect Information in Multivalued Logics. - Daniel Stamate (ISMVL, 2008)

A Bilattice Based Fixed Point Semantics for Integrating Imperfect Information. - Daniel Stamate (FICS, 2009)

Queries with Multivalued Logic-Based Semantics for Imperfect Information Fusion. - Daniel Stamate (ISMVL, 2010)

Quantitative Semantics for Uncertain Knowledge Bases. - Daniel Stamate (IPMU (3), 2012)

Imperfect Information Fusion Using Rules with Bilattice Based Fixpoint Semantics. - Daniel Stamate; Ida M. Pu (IPMU (3), 2012)

Scalable Distributed Genetic Algorithm for Data Ordering Problem with Inversion Using MapReduce. - Doina Logofatu; Daniel Stamate (AIAI, 2014)

Improving time-efficiency in blocking expanding ring search for mobile ad hoc networks. - Ida M. Pu; Daniel Stamate; Yuji Shen (J. Discrete Algorithms, 2014)

Sentiment and stock market volatility predictive modelling - A hybrid approach. - Rapheal Olaniyan; Daniel Stamate; Lahcen Ouarbya; Doina Logofatu (DSAA, 2015)

Social Web-Based Anxiety Index's Predictive Information on S&P 500 Revisited. - Rapheal Olaniyan; Daniel Stamate; Doina Logofatu (SLDS, 2015)

A Prediction Modelling and Pattern Detection Approach for the First-Episode Psychosis Associated to Cannabis Use. - Wajdi Alghamdi; Daniel Stamate; Katherine Vang; Daniel Stahl; Marco Colizzi; Giada Tripoli; Diego Quattrone; Olesya Ajnakina; Robin M. Murray; Marta Di Forti (ICMLA, 2016)

Particle Swarm Optimization Algorithms for Autonomous Robots with Leaders Using Hilbert Curves. - Doina Logofatu; Gil Sobol; Daniel Stamate (EANN, 2017)

A Novel Space Filling Curves Based Approach to PSO Algorithms for Autonomous Agents. - Doina Logofatu; Gil Sobol; Daniel Stamate; Kristiyan Balabanov (ICCCI (1), 2017)

Predictive Modelling Strategies to Understand Heterogeneous Manifestations of Asthma in Early Life. - Danielle Belgrave; Rachel Cassidy; Daniel Stamate; Adnan Custovic; Louise Fleming; Andrew Bush; Sejal Saglani (ICMLA, 2017)

Predicting Psychosis Using the Experience Sampling Method with Mobile Apps. - Daniel Stamate; Andrea Katrinecz; Wajdi Alghamdi; Daniel Stahl; Philippe Delespaul; Jim van Os; Sinan Guloksuz (ICMLA, 2017)

Data Science Challenges in Computational Psychiatry and Psychiatric Research. - Daniel Stahl; Daniel Stamate (DSAA, 2018)

A New Machine Learning Framework for Understanding the Link Between Cannabis Use and First-Episode Psychosis. - Wajdi Alghamdi; Daniel Stamate; Daniel Stahl; Alexander Zamyatin; Robin M. Murray; Marta Di Forti (eHealth, 2018)

On XLE Index Constituents' Social Media Based Sentiment Informing the Index Trend and Volatility Prediction. - Frédéric Maréchal; Daniel Stamate; Rapheal Olaniyan; Jiri Marek (ICCCI (2), 2018)

A Machine Learning Framework for Predicting Dementia and Mild Cognitive Impairment. - Daniel Stamate; Wajdi Alghamdi; Jeremy Ogg; Richard Hoile; Fionn Murtagh (ICMLA, 2018)

PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches. - Daniel Stamate; Wajdi Alghamdi; Daniel Stahl; Doina Logofatu; Alexander Zamyatin (AIAI, 2018)

Can Artificial Neural Networks Predict Psychiatric Conditions Associated with Cannabis Use? - Daniel Stamate; Wajdi Alghamdi; Daniel Stahl; Alexander Zamyatin; Robin M. Murray; Marta Di Forti (AIAI, 2018)

Predicting First-Episode Psychosis Associated with Cannabis Use with Artificial Neural Networks and Deep Learning. - Daniel Stamate; Wajdi Alghamdi; Daniel Stahl; Ida M. Pu; Fionn Murtagh; Danielle Belgrave; Robin M. Murray; Marta Di Forti (IPMU (3), 2018)

Predicting S&P 500 Based on Its Constituents and Their Social Media Derived Sentiment. - Rapheal Olaniyan; Daniel Stamate; Ida M. Pu; Alexander Zamyatin; Anna Vashkel; Frédéric Maréchal (ICCCI (1), 2019)

A regime-switching recurrent neural network model applied to wind time series. - Nikolay Y. Nikolaev; Evgueni N. Smirnov; Daniel Stamate; Robert Zimmer (Appl. Soft Comput., 2019)

Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment. - Daniel Stamate; Richard Smith; Ruslan Tsygancov; Rostislav Vorobev; John Langham; Daniel Stahl; David Reeves (AIAI (2), 2020)

Particle swarm optimization algorithms for autonomous robots with deterministic leaders using space filling movements. - Doina Logofatu; Gil Sobol; Christina Andersson; Daniel Stamate; Kristiyan Balabanov; Tymoteusz Cejrowski (Evol. Syst., 2020)

Predicting risk of dementia with machine learning and survival models using routine primary care records. - John Langham; Daniel Stamate; Charlotte A. Wu; Fionn Murtagh; Catharine Morgan; David Reeves; Darren Ashcroft; Evangelos Kontopantelis; Brian McMillan (BIBM, 2021)

Creating Ensembles of Generative Adversarial Network Discriminators for One-Class Classification. - Mihai Ermaliuc; Daniel Stamate; George D. Magoulas; Ida M. Pu (EANN, 2021)

A Machine Learning Approach for Predicting Deterioration in Alzheimer's Disease. - Henry Musto; Daniel Stamate; Ida M. Pu; Daniel Stahl (ICMLA, 2021)

A Two-Step Optimised BERT-Based NLP Algorithm for Extracting Sentiment from Financial News. - Rapheal Olaniyan; Daniel Stamate; Ida M. Pu (AIAI, 2021)

A Neural Network Approach to Estimating Color Reflectance with Product Independent Models. - Asei Akanuma; Daniel Stamate (ICANN (3), 2022)

Combining Cox Model and Tree-Based Algorithms to Boost Performance and Preserve Interpretability for Health Outcomes. - Diana Shamsutdinova; Daniel Stamate; Angus Roberts; Daniel Stahl (AIAI (2), 2022)

Predicting Risk of Dementia with Survival Machine Learning and Statistical Methods: Results on the English Longitudinal Study of Ageing Cohort. - Daniel Stamate; Henry Musto; Olesya Ajnakina; Daniel Stahl (AIAI (Workshops), 2022)

On a Survival Gradient Boosting, Neural Network and Cox PH Based Approach to Predicting Dementia Diagnosis Risk on ADNI. - Henry Musto; Daniel Stamate; Doina Logofatu; Lahcen Ouarbya (BIBM, 2023)

Predicting High vs Low Mother-Baby Synchrony with GRU-Based Ensemble Models. - Daniel Stamate; Riya Haran; Karolina Rutkowska; Pradyumna Davuloori; Evelyne Mercure; Caspar Addyman; Mark Tomlinson (ICANN (9), 2023)

Predicting Alzheimer's Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort. - Henry Musto; Daniel Stamate; Ida M. Pu; Daniel Stahl (ICCCI, 2023)

Predicting Colour Reflectance with Gradient Boosting and Deep Learning. - Asei Akanuma; Daniel Stamate; J. Mark Bishop (AIAI (1), 2023)

Joint Decision Making in Ant Colony Systems for Solving the Multiple Traveling Salesman Problem. - Mihaela Breaban; Raluca Necula; Dorel Lucanu; Daniel Stamate (KES, 2023)

Predicting Alzheimers Disease Diagnosis Risk over Time with Survival Machine Learning on the ADNI Cohort. - Henry Musto; Daniel Stamate; Ida M. Pu; Daniel Stahl (CoRR, 2023)

Ensembles of Bidirectional LSTM and GRU Neural Nets for Predicting Mother-Infant Synchrony in Videos. - Daniel Stamate; Pradyumna Davuloori; Doina Logofatu; Evelyne Mercure; Caspar Addyman; Mark Tomlinson (EANN, 2024)

Predicting Deterioration in Mild Cognitive Impairment with Survival Transformers, Extreme Gradient Boosting and Cox Proportional Hazard Modelling. - Henry Musto; Daniel Stamate; Doina Logofatu; Daniel Stahl (ICANN (8), 2024)

Variational Encoder Based Synthetic Alzheimer's Data Generation for Deep Learning, XGBoost and Statistical Survival Analysis. - Henry Musto; Daniel Stamate; Daniel Stahl (ICMLA, 2024)

Classifying Cognitive States of Alzheimer's Disease with Machine Learning Using Digital Biomarkers from the Bio-Hermes Study Cohort. - Eoin Houstoun; Daniel Stamate; Henry Musto; David Reeves; Catharine Morgan; Roxana Hutanu; Kalliopi Mavromati; Dorina Cadar; Daniel Stahl (AIAI (4), 2025)

Proteomics, Neuropsychological and Demographics Multimodal Machine Learning Approach to Alzheimer's Disease Prediction on the Bio-Hermes Study Cohort. - Henry Musto; Daniel Stamate; David Reeves; Catharine Morgan; Roxana Hutanu; Kalliopi Mavromati; Dorina Cadar; Daniel Stahl (AIAI (4), 2025)

Balancing accuracy and Interpretability: An R package assessing complex relationships beyond the Cox model and applications to clinical prediction. - Diana Shamsutdinova; Daniel Stamate; Daniel Stahl (Int. J. Medical Informatics, 2025)