EMERGE – GPM

mEdida y representación de flujos de inforMación en rEdes neuRonales biolóGicas y artificialEs

A pesar de su ya muy significativo impacto social y económico, la actual generación de Inteligencia Artificial (AI) se considera menos eficiente, demasiado especializada, reactiva y con memoria más limitada que la futura super AI general. Además, su consumo de potencia es cada vez más alto. En la búsqueda de una mejor AI, es urgente reducir su huella de carbono pero sin obstaculizar su desarrollo.

En EMERGE, proponemos repensar el aprendizaje automático desde el punto de vista de la Teoría de la Información basándonos en encontrar inspiración en la transmisión de información en las redes neuronales biológicas. Algunas de las herramientas básicas que utilizaremos han sido propuestas por nosotros en la última década y son capaces de realizar un seguimiento de la transferencia y pérdida de información a través de las capas de las redes neuronales.

Buscando una justificación alternativa de los principios de las redes neuronales profundas (DNN) que mejore su interpretabilidad, efectividad y eficiencia, volveremos a analizar modelos básicos bien establecidos de sus componentes (Restricted Boltzmann MachinesRBM, Deep Boltzmann Machines DBM y AutoEncodersAE) y que permitan allanar el camino para una nueva generación de Redes Neuronales Artificiales.

Primero, comenzaremos reescribiendo las RBMs como máquinas para propagar información y aplicaremos nuestras herramientas de Análisis de Conceptos Formales Informacionales para interpretar sus resultados. A continuación, relajaremos el modelo para considerar máquinas de Boltzmann genéricas como modelos de redes neuronales biológicas muy simples, como la del Caenorhabditis elegans. Despues aplicaremos los resultados a: 1) La evaluación e interpretación de máquinas de Boltzmann, Deep Boltzmann Machines y AutoEncoders; 2) La síntesis de nuevas arquitecturas basadas directamente en el transporte de información aplicadas a la exploración de escenas acústicas; 3) El análisis de redes neuronales biológicas que utilizan el paradigma anterior aplicadas a encontrar correlatos de comportamiento en las redes neuronales del C.elegans.

Objetivos

Objetivo general.

Desarrollar y evaluar modelos de inteligencia incorporada basados en datos utilizando modelos neuronales que operan sobre flujos de información y que contribuyan a encontrar soluciones mejores, más eficientes y sostenibles para la AI.

Objetivos específicos.

Objetivo específico teórico: Desarrollar y evaluar modelos basados en información que utilizan grafos ponderados y bipartitos con pesos y flujos que toman valores en semicuerpos positivos.

Objetivo específico de análisis de datos: Analizar los datos del conectoma de C.elegans y el comportamiento en un bucle situado con el uso de herramientas de análisis de flujo en grafos con valores en semi-cuerpos positivos.

Objetivo específico de modelado y síntesis: Sintetizar modelos de ML con valores en semi-cuerpos positivos para resolver una tarea de percepción y cognición artificial. En concreto nos centraremos en la tarea de exploración de una escena acústica.

Publicaciones

(En acceso abierto en nuestro repositorio institucional: https://e-archivo.uc3m.es/handle/10016/1591)

F. J. Valverde-Albacete, C. Peláez-Moreno, I. de las Peñas-Cabrera, P. Cordero-Ortega, and M. Ojeda-Aciego, “Formal Context Transforms,” Expert Systems with Applications (enviado), 2024.
[Bibtex]

@article{val:pel:de:cor:oje:24,
  title = {Formal {Context} {Transforms}},
  abstract = {Considering formal contexts (G, M, I) as bearers of information, we try to analyse Formal Concept Analysis (FCA) and the related processes of Formal Independence Analysis (FIA) and Formal Equivalence Analysis (FEA), in order to find the strengths and shortcomings of their information-eliciting capabilities. This is an important concern when using any of these forms of analysis as a data analysis technique over relational data. We come to the conclusion that FCA only deals with a limited type of information and we seek to expand these capabilities. Therefore we propose the concept of context transform as a way to elicit new information types from contexts that we call information qualia. We apply this concept of context transform to explain what are the affordances of FCA, FIA and FEA and how we may expect other formal analysis of different information qualia to arise from a formal context.},
  language = {english},
  journal = {Expert Systems with Applications (enviado)},
  author = {Valverde-Albacete, Francisco J and Peláez-Moreno, Carmen and de las Peñas-Cabrera, Inmaculada and Cordero-Ortega, Pablo and Ojeda-Aciego, Manuel},
  year = {2024},
  note = {tex.date-added: 2024-05-17 20:17:11 +0200
tex.date-modified: 2024-05-17 20:17:11 +0200},
}

F. J. Valverde-Albacete and C. Peláez-Moreno, “A Formalization of Multilabel Classification in Terms of Lattice Theory and Information Theory: Concerning Datasets,” Mathematics, vol. 12, iss. 2, p. 346, 2024.
[Bibtex]

@article{valverde-albaceteFormalizationMultilabelClassification2024a,
  title = {A {Formalization} of {Multilabel} {Classification} in {Terms} of {Lattice} {Theory} and {Information} {Theory}: {Concerning} {Datasets}},
  volume = {12},
  issn = {2227-7390},
  shorttitle = {A {Formalization} of {Multilabel} {Classification} in {Terms} of {Lattice} {Theory} and {Information} {Theory}},
  url = {https://www.mdpi.com/2227-7390/12/2/346},
  doi = {10.3390/math12020346},
  abstract = {Multilabel classification is a recently conceptualized task in machine learning. Contrary to most of the research that has so far focused on classification machinery, we take a data-centric approach and provide an integrative framework that blends qualitative and quantitative descriptions of multilabel data sources. By combining lattice theory, in the form of formal concept analysis, and entropy triangles, obtained from information theory, we explain from first principles the fundamental issues of multilabel datasets such as the dependencies of the labels, their imbalances, or the effects of the presence of hapaxes. This allows us to provide guidelines for resampling and new data collection and their relationship with broad modelling approaches. We have empirically validated our framework using 56 open datasets, challenging previous characterizations that prove that our formalization brings useful insights into the task of multilabel classification. Further work will consider the extension of this formalization to understand the relationship between the data sources, the classification methods, and ways to assess their performance.},
  language = {english},
  number = {2},
  urldate = {2024-01-21},
  journal = {Mathematics},
  author = {Valverde-Albacete, Francisco J. and Peláez-Moreno, Carmen},
  month = jan,
  year = {2024},
  note = {Publisher: Multidisciplinary Digital Publishing Institute},
  keywords = {entropy balances, formal concept analysis, information sources, meta-analysis, multilabel classification, multilabel datasets},
  pages = {346},
  file = {Valverde-Albacete_Pelaez-Moreno_2024_A Formalization of Multilabel Classification in Terms of Lattice Theory and.pdf:/Users/carmen/Documents/Zotero/Mathematics/2024/Valverde-Albacete_Pelaez-Moreno_2024_A Formalization of Multilabel Classification in Terms of Lattice Theory and.pdf:application/pdf},
}

Ponencias en congresos y charlas

E. Reyner-Fuentes, C. Peláez-Moreno, and J. Valverde-Albacete, “Discovering the Structure of Odorants in Caenorhabditis elegans using Formal Concept Analysis,” in CONCEPTS (enviado), Cádiz, Spain, 2024.
[Bibtex]

@inproceedings{rey:pel:val:24,
  address = {Cádiz, Spain},
  title = {Discovering the {Structure} of {Odorants} in {Caenorhabditis} elegans using {Formal} {Concept} {Analysis}},
  abstract = {Embodied and Embedded cognition posits that animals act by operating a sensory-motor loop over an environment through the concourse of their nervous systems. A notable challenge in studying the nervous system lies in the absence of a model of its sensorium, the mechanism whereby an organism perceives its surroundings. This paper addresses the inquiry into the perception mechanisms of Caenorhabditis elegans as a model organism. To this end, we have delimited the perceptual domain to 23 distinct odorants, for which we have the corresponding neural activity data from the 11 pairs of sensory neurons. This paper elucidates how the integration of various FCA-related methodologies—specifically, K-FCA max-plus and min-plus analyses, as well as cosine distance calculations—allows for the obtention of a representation of the perceptual framework of C. elegans. Additionally, we propose avenues for further refinement, including the consideration of the idempotent singular value decomposition within the FCA framework to improve said perceptual representations.},
  language = {english},
  booktitle = {CONCEPTS (enviado)},
  author = {Reyner-Fuentes, Emma and Peláez-Moreno, Carmen and Valverde-Albacete, J},
  year = {2024},
  conference = {Concepts},
  note = {tex.date-added: 2024-05-17 20:25:59 +0200
tex.date-modified: 2024-05-17 20:25:59 +0200},
}

F. J. Valverde-Albacete and C. Peláez-Moreno, “The Rényi Entropies Operate in Positive Semifields,” in CSH Workshop: The Rényi entropy in machine learning: Whither now?, Complexity Science Hub, Vienna, 2023.
[Bibtex]

@inproceedings{val:pel:23,
  title = {The {Rényi} {Entropies} {Operate} in {Positive} {Semifields}},
  abstract = {We set out to demonstrate that the Rényi entropies are better thought of as operating in a type of non-linear semiring called a positive semifield. We show how the Rényi's postulates lead to Pap's g-calculus where the functions carrying out the domain transformation are Rényi's information function and its inverse. In its turn, Pap's g-calculus under Rényi's information function transforms the set of positive reals into a family of semirings where “standard” product has been transformed into sum and “standard” sum into a power-emphasized sum. Consequently, the transformed product has an inverse whence the structure is actually that of a positive semifield. Instances of this construction lead to idempotent analysis and tropical algebra as well as to less exotic structures. We conjecture that this is one of the reasons why tropical algebra procedures, like the Viterbi algorithm of dynamic programming, morphological processing, or neural networks are so successful in computational intelligence applications. But also, why there seem to exist so many computational intelligence procedures to deal with “information” at large.},
  url = {https://www.csh.ac.at/event/csh-workshop-the-renyi-entropy-in-machine-learning-whither-now/},
  author = {Valverde-Albacete, Francisco J. and Peláez-Moreno, Carmen},
  month = jul,
  year = {2023},
  booktitle = {CSH Workshop: {The Rényi entropy in machine learning: Whither now?}},
  address = {Complexity Science Hub, Vienna}
}

F. J. Valverde-Albacete and C. Peláez-Moreno, “Recovering Semantics in Information Theory,” in HARMONIC’23, Osuna, Sevilla, 2023.
[Bibtex]

@inproceedings{val:pel:23a,
  title = {Recovering {Semantics} in {Information} {Theory}},
  author = {Valverde-Albacete, Francisco J and Peláez-Moreno, Carmen},
  month = oct,
  year = {2023},
  booktitle = {HARMONIC'23},
  address = {Osuna, Sevilla}
}

F. J. Valverde-Albacete and C. Peláez-Moreno, “Sobre el Análisis en Conceptos Formales como Modelo de Semántica Cognitiva en IA,” in Bienal RSME, Pamplona, Spain, 2024.
[Bibtex]

@inproceedings{val:pel:24a,
  title = {Sobre el {Análisis} en {Conceptos} {Formales} como {Modelo} de {Semántica} {Cognitiva} en {IA}},
  author = {Valverde-Albacete, Francisco J and Peláez-Moreno, Carmen},
  month = jan,
  booktitle = {Bienal RSME},
  year = {2024},
  address = {Pamplona, Spain}
}

C. Montero-Ramírez, E. Rituerto-González, and C. Peláez-Moreno, “Exploring Audio Representations for Soundscape Classification in Daily-life Scenarios of Gender-based Violence Victims,” in INTERSPEECH 2024, 2024.
[Bibtex]

@inproceedings{montero-ramirezExploringAudioRepresentations2024,
  title = {Exploring {Audio} {Representations} for {Soundscape} {Classification} in {Daily}-life {Scenarios} of {Gender}-based {Violence} {Victims}},
  abstract = {Soundscapes are a fundamental component of the context of real-world scenarios. Characterizing them can be a determining factor in detecting risky situations, as in the cases of gender-based violence. In spite of the great advances of current deep learning techniques in the field of Acoustic Scene Classification (ASC), it has not yet been deeply studied how ASC techniques perform in the real-world scenarios of our daily lives. This study aims to evaluate the performance of state-of-the-art audio representations for ASC in {\textbackslash}textit\{WELIVE\}, an in-the-wild dataset that contains audio signals from the daily lives of gender-based violence victims. Our results show that the robustness of ASC methods is a highly difficult challenge in such situations with handcrafted features together with pretrained models have the greatest potential to succeed. This work contributes to the study of real-world soundscape classification, which can assist in the detection of risky situations, among other applications.},
  language = {english},
  booktitle = {{INTERSPEECH} 2024},
  publisher = {ISCA},
  author = {Montero-Ramírez, Claudia and Rituerto-González, Esther and Peláez-Moreno, Carmen},
  year = {2024},
  note = {tex.eventtitle: INTERSPEECH 2024},
  keywords = {Conferences},
}

C. Peláez-Moreno and F. Valverde-Albacete, “Opening the black box of machine learning with entropy triangles,” in CSH Workshop: The Rényi entropy in machine learning: Whither now?, Complexity Science Hub, Vienna, 2023.
[Bibtex]

@inproceedings{pelaez-morenoOpeningBlackBox2023,
  title = {Opening the black box of machine learning with entropy triangles},
  url = {https://www.csh.ac.at/event/csh-workshop-the-renyi-entropy-in-machine-learning-whither-now/},
  author = {Peláez-Moreno, Carmen and Valverde-Albacete, Francisco},
  month = jul,
  year = {2023},
  booktitle = {CSH Workshop: {The Rényi entropy in machine learning: Whither now?}},
  address = {Complexity Science Hub, Vienna}
}

C. Peláez-Moreno, “Sesgos de género en la Inteligencia Artificial,” in La incorporación de la perspectiva de género en las STEM, Madrid, Spain, 2022.
[Bibtex]

@inproceedings{pelaez-morenoSesgosGeneroInteligencia2022,
  title = {Sesgos de género en la {Inteligencia} {Artificial}},
  url = {https://eventos.uc3m.es/88781/detail/la-incorporacion-de-la-perspectiva-de-genero-en-las-stem.html},
  abstract = {Workshop La incorporación de la perspectiva de género en las STEM PRESENCIAL 23 de noviembre Aula de Grados - Campus Leganes Inscripciones https://tinyurl.com/26te4zxv Este seminario forma parte del ciclo LA PERSPECTIVA DE GÉNERO EN LOS PROCESOS DE FORMACIÓN Y EVALUACIÓN DEL SISTEMA EDUCATIVO: INVESTIGACIÓN, BUENAS PRÁCTICAS Y RETOS DE FUTURO financiado por el Intituto de las Mujeres. En este workshop pretendemos crear un espacio para compartir y discutir diferentes propuestas de incorporación de la perspectiva de género en las STEM. Con estas actividades, el Instituto de Estudios de Género tiene por objetivo principal impulsar la incorporación de la perspectiva de género en todos los procesos de formación, investigación y evaluación de la Universidad. Existen sesgos sexistas y androcéntricos en los conocimientos y en los propios contenidos de las ciencias y de los significados, que se plasman en la práctica de la investigación científica, pero que también van más allá y se trasladan a las prácticas del ejercicio profesional. En “La perspectiva de género en los procesos de formación y evaluación del sistema educativo: investigación, buenas prácticas y retos de futuro” se visibilizará la gran producción que está habiendo en la investigación universitaria, especialmente entre las nuevas generaciones de investigadores e investigadoras, así como la posibilidad de cambio real que supone la integración de la perspectiva de género en los procesos de formación y evaluación del ámbito universitario. Inscripciones https://tinyurl.com/26te4zxv},
  language = {english},
  urldate = {2024-01-09},
  author = {Peláez-Moreno, Carmen},
  month = nov,
  year = {2022},
  booktitle = {La incorporación de la perspectiva de género en las STEM},
  address = {Madrid, Spain},
  note = {tex.venue: Universidad Carlos III de Madrid},
}

E. Reyner-Fuentes, E. Rituerto González, C. Luis-Mingueza, C. Peláez-Moreno, and C. López-Ongil, “Detecting Gender-based Violence aftereffects from Emotional Speech Paralinguistic Features,” in IberSPEECH 2022, 2022, pp. 96-100.
[Bibtex]

@inproceedings{reyner-fuentesDetectingGenderbasedViolence2022,
  title = {Detecting {Gender}-based {Violence} aftereffects from {Emotional} {Speech} {Paralinguistic} {Features}},
  url = {https://www.isca-speech.org/archive/iberspeech_2022/reynerfuentes22_iberspeech.html},
  doi = {10.21437/IberSPEECH.2022-20},
  abstract = {Speech is known to provide information regarding the person speaking, such as their gender, identity, emotions, and even disorders or trauma. In this paper we aim to answer the following question, can women who have suffered from gender-based violence (GBV) be distinguished from those who have not, just by using speech paralinguistic cues? In this work, we intend to demonstrate whether there exist measurable differences between the emotional expression in the voice of GBV victims (GBVV) and non-victims (Non-GBVV). The present study was carried out in the framework of the project EMPATIA-CM, whose aim is to understand the reaction of GBVV to dangerous situations and develop automatic mechanisms to protect them. For this purpose, we use data collected and partly published from the WEMAC Database, a multimodal database containing physiological and speech data from women who have and have not suffered from GBV while visualizing different emotion-eliciting video clips. With the performed analysis, it is proven that such differences exist indeed and, therefore, that suffering from GBV alters the way women react to the same emotion eliciting stimulus in terms of physical variables, specifically certain voice features.},
  language = {english},
  urldate = {2023-12-04},
  booktitle = {{IberSPEECH} 2022},
  publisher = {ISCA},
  author = {Reyner-Fuentes, Emma and Rituerto González, Esther and Luis-Mingueza, Clara and Peláez-Moreno, Carmen and López-Ongil, Celia},
  month = nov,
  year = {2022},
  note = {tex.eventtitle: IberSPEECH 2022},
  keywords = {Conferences},
  pages = {96--100},
  file = {Reyner-Fuentes et al_2022_Detecting Gender-based Violence aftereffects from Emotional Speech.pdf:/Users/carmen/Documents/Zotero/ISCA/2022/Reyner-Fuentes et al_2022_Detecting Gender-based Violence aftereffects from Emotional Speech.pdf:application/pdf},
}

E. Reyner-Fuentes, E. Rituerto-González, I. Trancoso, and C. Peláez-Moreno, “Prediction of the Gender-based Violence Victim Condition using Speech: What do Machine Learning Models rely on?,” in INTERSPEECH 2023, 2023, pp. 1768-1772.
[Bibtex]

@inproceedings{reyner-fuentesPredictionGenderbasedViolence2023,
  title = {Prediction of the {Gender}-based {Violence} {Victim} {Condition} using {Speech}: {What} do {Machine} {Learning} {Models} rely on?},
  shorttitle = {Prediction of the {Gender}-based {Violence} {Victim} {Condition} using {Speech}},
  url = {https://www.isca-speech.org/archive/interspeech_2023/reynerfuentes23_interspeech.html},
  doi = {10.21437/Interspeech.2023-1771},
  abstract = {Women who have experienced gender-based violence (GBV) are at an increased risk of developing mental illnesses such as depression, anxiety, and post-traumatic stress disorder (PTSD). Recently, Artificial Intelligence (AI) has provided new tools to assist in mental health clinical diagnosis, including speech-based detection. However, there is not much work done on the GBV victim (GBVV) condition detection. This study aims to identify specific speech features that aid this detection, analyse the relationship of such results with the user’s psychological evaluation, and evaluate whether the models rely on the speaker identity or self-reported emotions to predict the GBVV condition. Our results indicate that it is possible to distinguish GBVV with controlled sequelae from non-victims, which may suggest that such differentiation for GBVV with more severe mental aftereffects–such as PTSD–may be even more meaningful. We believe that our work can help future mental health AI therapy assistants.},
  language = {english},
  urldate = {2023-11-02},
  booktitle = {{INTERSPEECH} 2023},
  publisher = {ISCA},
  author = {Reyner-Fuentes, Emma and Rituerto-González, Esther and Trancoso, Isabel and Peláez-Moreno, Carmen},
  month = aug,
  year = {2023},
  note = {tex.eventtitle: INTERSPEECH 2023},
  keywords = {Conferences},
  pages = {1768--1772},
  file = {Reyner-Fuentes et al_2023_Prediction of the Gender-based Violence Victim Condition using Speech.pdf:/Users/carmen/Documents/Zotero/ISCA/2023/Reyner-Fuentes et al_2023_Prediction of the Gender-based Violence Victim Condition using Speech.pdf:application/pdf},
}

E. Rituerto-González, C. Luis Mingueza, and C. Peláez-Moreno, “Affective acoustic scene analysis to detect threatening scenarios,” in 53º Congreso Español De Acústica -TECNIACUSTICA 2022-, 2022.
[Bibtex]

@inproceedings{rituerto-gonzalezAffectiveAcousticScene2022,
  title = {Affective acoustic scene analysis to detect threatening scenarios},
  booktitle = {53º {Congreso} {Español} {De} {Acústica} -{TECNIACUSTICA} 2022-},
  publisher = {Sociedad Española de Acústica},
  author = {Rituerto-González, Esther and Luis Mingueza, Clara and Peláez-Moreno, Carmen},
  year = {2022},
  note = {Place: Elche, Spain
tex.eventtitle: 53º CONGRESO ESPAÑOL DE ACÚSTICA -TECNIACUSTICA 2022-},
  keywords = {Conferences},
  file = {Rituerto-Gonzalez et al_2022_Affective acoustic scene analysis to detect threatening scenarios.pdf:/Users/carmen/Documents/Zotero/Sociedad Española de Acústica/2022/Rituerto-Gonzalez et al_2022_Affective acoustic scene analysis to detect threatening scenarios.pdf:application/pdf},
}

F. J. Valverde-Albacete, C. Peláez-Moreno, I. P. Cabrera, P. Cordero, and M. Ojeda-Aciego, “Can FCA Provide a Framework for AGI?,” in 10th International Workshop “What can FCA do for Artificial Intelligence?”, Vienna, Austria, 2022, p. 6.
[Bibtex]

@inproceedings{valverde-albaceteCanFCAProvide2022,
  title = {Can {FCA} {Provide} a {Framework} for {AGI}?},
  volume = {3233},
  abstract = {This paper is an attempt at bridging two strains of research being developed by the authors: a theory of information flows to subserve intelligence and a theory of affordances for the modelling of Embodied, Embedded, Extended and Enacted Computational Intelligence as provided by FCA. We list previous successes, present challenges, and future avenues of research that suggest themselves.},
  language = {english},
  booktitle = {10th {International} {Workshop} "{What} can {FCA} do for {Artificial} {Intelligence}?"},
  publisher = {CEUR},
  author = {Valverde-Albacete, Francisco J and Peláez-Moreno, Carmen and Cabrera, Inma P and Cordero, Pablo and Ojeda-Aciego, Manuel},
  year = {2022},
  address = {Vienna, Austria},
  note = {Place: Vienna Austria
tex.eventtitle: FCA4AI 2022},
  keywords = {Conferences},
  pages = {6},
  file = {Valverde-Albacete et al_2022_Can FCA Provide a Framework for AGI.pdf:/Users/carmen/Documents/Zotero/CEUR/2022/Valverde-Albacete et al_2022_Can FCA Provide a Framework for AGI.pdf:application/pdf}
}

F. J. Valverde-Albacete and C. Peláez-Moreno, “Filosofía de la Tecnología y de la Inteligencia Artificial,” in XXII Semana de la Ciencia y la Innovación de Madrid, Madrid, Spain, 2022.
[Bibtex]

@inproceedings{valverde-albaceteFilosofiaTecnologiaInteligencia2022,
  title = {Filosofía de la {Tecnología} y de la {Inteligencia} {Artificial}},
  url = {https://eventos.urjc.es/89439/detail/filosofia-de-la-tecnologia-y-de-la-inteligencia-artificial.html},
  language = {spanish},
  author = {Valverde-Albacete, Francisco José and Peláez-Moreno, Carmen},
  month = nov,
  year = {2022},
  booktitle = {XXII Semana de la Ciencia y la Innovación de Madrid},
  address = {Madrid, Spain},
  note = {tex.eventtitle: XXII Semana de la Ciencia y la Innovación de Madrid
tex.venue: Universidad Rey Juan Carlos}
}

Tesis

V. Bohach, “Exploreing the connectome of Caenorhabditis elegans,” Undergraduate PhD Thesis, Fuenlabrada, 2024.
[Bibtex]

@phdthesis{boh:24,
  address = {Fuenlabrada},
  type = {Undergraduate},
  title = {Exploreing the connectome of Caenorhabditis elegans},
  language = {english},
  school = {Universidad Rey Juan Carlos},
  author = {Bohach, Viktoriya},
  month = mar,
  year = {2024},
  note = {tex.date-added: 2024-05-17 20:19:45 +0200
tex.date-modified: 2024-05-17 20:19:45 +0200},
}

M. Carrasco-Ávila and C. Peláez-Moreno, “Computación bio-inspirada para aplicaciones musicales,” Undergraduate PhD Thesis, Leganés, Madrid, Spain, 2023.
[Bibtex]

@phdthesis{carrasco-avilaComputacionBioinspiradaPara2023,
  address = {Leganés, Madrid, Spain},
  type = {Undergraduate},
  title = {Computación bio-inspirada para aplicaciones musicales},
  school = {Universidad Carlos III de Madrid (TFG)},
  author = {Carrasco-Ávila, Micaela and Peláez-Moreno, Carmen},
  year = {2023},
  keywords = {Conferences},
}

A. Casado-del-Rincón and C. Peláez-Moreno, “Exploring the multi-layer connectome of c.elegans: Integrating monoamide and neuropeptide layers into community detection and functional analysis,” Undergraduate PhD Thesis, Leganés, Madrid, Spain, 2023.
[Bibtex]

@phdthesis{casado-del-rinconExploringMultilayerConnectome2023,
  address = {Leganés, Madrid, Spain},
  title = {Exploring the multi-layer connectome of c.elegans: {Integrating} monoamide and neuropeptide layers into community detection and functional analysis},
    type = {Undergraduate},
  school = {Universidad Carlos III de Madrid (TFG)},
  author = {Casado-del-Rincón, Alba and Peláez-Moreno, Carmen},
  year = {2023},
  keywords = {Conferences},
}

C. Luis-Mingueza and C. Peláez-Moreno, “Bias and interpretability in violence scene detection from acoustic signals,” Master’s PhD Thesis, Leganés, Madrid, Spain, 2022.
[Bibtex]

@phdthesis{luis-minguezaBiasInterpretabilityViolence2022,
  address = {Leganés, Madrid, Spain},
  title = {Bias and interpretability in violence scene detection from acoustic signals},
  school = {Universidad Carlos III de Madrid (TFM)},
    type = {Master's},
  author = {Luis-Mingueza, Clara and Peláez-Moreno, Carmen},
  year = {2022},
  keywords = {Conferences},
}

J. R. Manjavacas-Maceiras and C. Peláez-Moreno, “Brain-inspired computing with spiking neural networks,” Undergraduate PhD Thesis, Leganés, Madrid, Spain, 2022.
[Bibtex]

@phdthesis{manjavacas-maceirasBraininspiredComputingSpiking2022,
  address = {Leganés, Madrid, Spain},
  title = {Brain-inspired computing with spiking neural networks},
  school = {Universidad Carlos III de Madrid (TFG)},
    type = {Undergraduate},
  author = {Manjavacas-Maceiras, José Ramón and Peláez-Moreno, Carmen},
  year = {2022},
  keywords = {Conferences},
}

C. Montero-Ramírez, E. Rituerto-González, and C. Peláez-Moreno, “Spatio-temporal Latent Representations for the Analysis of Acoustic Scenes in-the-Wild,” Master’s PhD Thesis, Leganés, Madrid, Spain, 2023.
[Bibtex]

@phdthesis{montero-ramirezSpatiotemporalLatentRepresentations2023,
  address = {Leganés, Madrid, Spain},
  title = {Spatio-temporal {Latent} {Representations} for the {Analysis} of {Acoustic} {Scenes} in-the-{Wild}},
  school = {Universidad Carlos III de Madrid (TFM)},
    type = {Master's},
  author = {Montero-Ramírez, Claudia and Rituerto-González, Esther and Peláez-Moreno, Carmen},
  year = {2023},
  keywords = {Conferences},
}

E. Reyner-Fuentes, “Redes neuronales bioinspiradas basadas en flujos informacionales / Information theoretical Bio-inspired neural networks,” doctoral thesis (fecha prevista) PhD Thesis, 2026.
[Bibtex]

@phdthesis{reyner-fuentesRedesNeuronalesBioinspiradas2026,
  type = {doctoral thesis (fecha prevista)},
  title = {Redes neuronales bioinspiradas basadas en flujos informacionales / {Information} theoretical {Bio}-inspired neural networks},
  url = {https://e-archivo.uc3m.es/handle/10016/36623},
  language = {english},
  urldate = {2024-01-09},
  author = {Reyner-Fuentes, Emma},
  year = {2026},
  note = {tex.namea: Peláez-Moreno, Carmen and Valverde-Albacete, F. J.
tex.nameatype: collaborator},
  file = {36623:/Users/carmen/Zotero/storage/5D4D94GM/36623.html:text/html},
}

Fechas de ejecución: 01/09/2022-31/08/2025

Financiado por: MICIU/AEI /10.13039/501100011033 y por FEDER, UE.