DNA based molecular computation: Template-template interactions in PCR. - Peter D. Kaplan; Guillermo A. Cecchi; Albert Libchaber (DNA Based Computers, 1996)

Unsupervised Learning and Adaptation in a Model of Adult Neurogenesis. - Guillermo A. Cecchi; Leopoldo T. Petreanu; Arturo Alvarez-Buylla; Marcelo O. Magnasco (J. Comput. Neurosci., 2001)

Simulation Infrastructure for Modeling Large Scale Neural Systems. - Charles C. Peck; James R. Kozloski; A. Ravishankar Rao; Guillermo A. Cecchi (International Conference on Computational Science, 2003)

A model of the formation of a self-organized cortical representation of color. - A. Ravishankar Rao; Guillermo A. Cecchi; Charles Peck 001; James R. Kozloski (Human Vision and Electronic Imaging, 2005)

Evaluation of the Effect of Input Stimuli on the Quality of Orientation Maps Produced Through Self Organization. - A. Ravishankar Rao; Guillermo A. Cecchi; Charles Peck 001; James R. Kozloski (SCIA, 2005)

Inference and segmentation in cortical processing. - Yuan Liu; Guillermo A. Cecchi; A. Ravishankar Rao; James R. Kozloski; Charles C. Peck (Human Vision and Electronic Imaging, 2006)

An optimization approach to achieve unsupervised segmentation and binding in a dynamical network. - A. Ravishankar Rao; Guillermo A. Cecchi; Charles C. Peck; James R. Kozloski (IJCNN, 2006)

Network-Related Challenges and Insights from Neuroscience. - Charles Peck 001; James R. Kozloski; Guillermo A. Cecchi; Sean L. Hill; Felix Schürmann; Henry Markram; Ravi Rao (BIOWIRE, 2007)

Cortical representation of information about visual attributes: one network or many? - Youping Xiao; Ravi Rao; Guillermo A. Cecchi; Ehud Kaplan (IJCNN, 2007)

Topographic Infomax in a Neural Multigrid. - James R. Kozloski; Guillermo A. Cecchi; Charles Peck 001; A. Ravishankar Rao (ISNN (2), 2007)

Emergence of Topographic Cortical Maps in a Parameterless Local Competition Network. - A. Ravishankar Rao; Guillermo A. Cecchi; Charles Peck 001; James R. Kozloski (ISNN (2), 2007)

Statistics of natural scenes and the cortical representation of color. - Guillermo A. Cecchi; A. Ravishankar Rao; Youping Xiao; Ehud Kaplan (Human Vision and Electronic Imaging, 2008)

Spatio-temporal Dynamics during Perceptual Processing in an Oscillatory Neural Network. - A. Ravishankar Rao; Guillermo A. Cecchi (ICANN (2), 2008)

Closed-form supervised dimensionality reduction with generalized linear models. - Irina Rish; Genady Grabarnik; Guillermo A. Cecchi; Francisco Pereira 001; Geoffrey J. Gordon (ICML, 2008)

Efficient segmentation in multi-layer oscillatory networks. - A. Ravishankar Rao; Guillermo A. Cecchi; Charles C. Peck; James R. Kozloski (IJCNN, 2008)

Inferring brain dynamics using granger causality on fMRI data. - Guillermo A. Cecchi; Rahul Garg 001; A. Ravishankar Rao (ISBI, 2008)

Improved mapping of information distribution across the cortical surface with the support vector machine. - Youping Xiao; Ravi Rao; Guillermo A. Cecchi; Ehud Kaplan (Neural Networks, 2008)

Unsupervised Segmentation With Dynamical Units. - A. Ravishankar Rao; Guillermo A. Cecchi; Charles C. Peck; James R. Kozloski (IEEE Trans. Neural Networks, 2008)

Self-Organizing Map Simulations Confirm Similarity of Spatial Correlation Structure in Natural Images and Cortical Representations. - A. Ravishankar Rao; Guillermo A. Cecchi (ICANN (1), 2009)

An optimization approach to understanding structure-function relationships in the visual cortex. - A. Ravishankar Rao; Guillermo A. Cecchi (IJCNN, 2009)

A Cluster Overlap Measure for Comparison of Activations in fMRI Studies. - Guillermo A. Cecchi; Rahul Garg 001; A. Ravishankar Rao (MICCAI (1), 2009)

Discriminative Network Models of Schizophrenia. - Guillermo A. Cecchi; Irina Rish; Benjamin Thyreau; Bertrand Thirion; Marion Plaze; Marie-Laure Paillère-Martinot; Catherine Martelli; Jean-Luc Martinot; Jean-Baptiste Poline (NIPS, 2009)

Prediction and interpretation of distributed neural activity with sparse models. - Melissa K. Carroll; Guillermo A. Cecchi; Irina Rish; Rahul Garg 001; A. Ravishankar Rao (NeuroImage, 2009)

Sparse Regression Models of Pain Perception. - Irina Rish; Guillermo A. Cecchi; Marwan N. Baliki; Apkar Vania Apkarian (Brain Informatics, 2010)

Investigating the variation of orientation tuning in a computational model of the visual cortex. - A. Ravishankar Rao; Guillermo A. Cecchi (IJCNN, 2010)

The emergence of the modern concept of introspection: a quantitative linguistic analysis. - Iván Raskovsky; Diego Fernández Slezak; Carlos Diuk; Guillermo A. Cecchi (NAACL (Young Investigators Workshop), 2010)

An objective function utilizing complex sparsity for efficient segmentation in multi-layer oscillatory networks. - A. Ravishankar Rao; Guillermo A. Cecchi (Int. J. Intell. Comput. Cybern., 2010)

The effects of feedback and lateral connections on perceptual processing: A study using oscillatory networks. - A. Ravishankar Rao; Guillermo A. Cecchi (IJCNN, 2011)

Brain as a self-predictor: Sparse full-brain auto-regressive modeling in fMRI. - Rahul Garg 001; Guillermo A. Cecchi; A. Ravishankar Rao (ISBI, 2011)

A spatio-temporal support vector machine searchlight for fMRI analysis. - A. Ravishankar Rao; Rahul Garg 001; Guillermo A. Cecchi (ISBI, 2011)

Fast computation of functional networks from fMRI activity: a multi-platform comparison. - A. Ravishankar Rao; Rajesh Bordawekar; Guillermo A. Cecchi (Image Processing, 2011)

Full-brain auto-regressive modeling (FARM) using fMRI. - Rahul Garg 001; Guillermo A. Cecchi; A. Ravishankar Rao (NeuroImage, 2011)

Sparse regression analysis of task-relevant information distribution in the brain. - Irina Rish; Guillermo A. Cecchi; Kyle Heuton; Marwan N. Baliki; Apkar Vania Apkarian (Image Processing, 2012)

Variable Selection for Gaussian Graphical Models. - Jean Honorio; Dimitris Samaras; Irina Rish; Guillermo A. Cecchi (AISTATS, 2012)

Predictive Dynamics of Human Pain Perception. - Guillermo A. Cecchi; Lejian Huang; Javeria Ali Hashmi; Marwan N. Baliki; María V. Centeno; Irina Rish; Apkar Vania Apkarian (PLoS Comput. Biol., 2012)

Multi-sensory integration using sparse spatio-temporal encoding. - A. Ravishankar Rao; Guillermo A. Cecchi (IJCNN, 2013)

Capacity limits in oscillatory networks: Implications for sensory coding. - A. Ravishankar Rao; Guillermo A. Cecchi (IJCNN, 2013)

Linking human brain local activity fluctuations to structural and functional network architectures. - Alex T. Baria; A. Mansour; Lejian Huang; Marwan N. Baliki; Guillermo A. Cecchi; M.-Marsel Mesulam; Apkar Vania Apkarian (NeuroImage, 2013)

Automated Speech Analysis for Psychosis Evaluation. - Facundo Carrillo; Natalia Mota; Mauro Copelli; Sidarta Ribeiro; Mariano Sigman; Guillermo A. Cecchi; Diego Fernández Slezak (MLINI@NIPS, 2014)

Spatial localization of the first and last enzymes effectively connects active metabolic pathways in bacteria. - Pablo Meyer 001; Guillermo A. Cecchi; Gustavo Stolovitzky (BMC Syst. Biol., 2014)

Fast Distributed Dynamics of Semantic Networks via Social Media. - Facundo Carrillo; Guillermo A. Cecchi; Mariano Sigman; Diego Fernández Slezak (Comput. Intell. Neurosci., 2015)

Evaluating effects of methylphenidate on brain activity in cocaine addiction: a machine-learning approach. - Irina Rish; Pouya Bashivan; Guillermo A. Cecchi; Rita Z. Goldstein (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2016)

Emotional Intensity analysis in Bipolar subjects. - Facundo Carrillo; Natalia Mota; Mauro Copelli; Sidarta Ribeiro; Mariano Sigman; Guillermo A. Cecchi; Diego Fernández Slezak (CoRR, 2016)

The ontogeny of discourse structure mimics the development of literature. - Natalia Bezerra Mota; Sylvia Pinheiro; Mariano Sigman; Diego Fernández Slezak; Guillermo A. Cecchi; Mauro Copelli; Sidarta Ribeiro (CoRR, 2016)

Bandit Models of Human Behavior: Reward Processing in Mental Disorders. - Djallel Bouneffouf 001; Irina Rish; Guillermo A. Cecchi (AGI, 2017)

Using Automated Metaphor Identification to Aid in Detection and Prediction of First-Episode Schizophrenia. - E. Dario Gutiérrez; Guillermo A. Cecchi; Cheryl Corcoran; Philip R. Corlett (EMNLP, 2017)

Context Attentive Bandits: Contextual Bandit with Restricted Context. - Djallel Bouneffouf 001; Irina Rish; Guillermo A. Cecchi; Raphaël Féraud (IJCAI, 2017)

Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. - Sahil Garg; Irina Rish; Guillermo A. Cecchi; Aurélie C. Lozano (IJCAI, 2017)

Phonological Markers of Oxytocin and MDMA Ingestion. - Carla Agurto; Raquel Norel; Rachel Ostrand; Gillinder Bedi; Harriet de Wit; Matthew J. Baggott; Matthew G. Kirkpatrick; Margaret Wardle; Guillermo A. Cecchi (INTERSPEECH, 2017)

Learning discriminative functional network features of schizophrenia. - Mina Gheiratmand; Irina Rish; Guillermo A. Cecchi; Matthew R. G. Brown; Russell Greiner; Pouya Bashivan; Pablo Polosecki; Serdar M. Dursun (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2017)

ProtoDash: Fast Interpretable Prototype Selection. - Karthik S. Gurumoorthy; Amit Dhurandhar; Guillermo A. Cecchi (CoRR, 2017)

Efficient Representation for Natural Language Processing via Kernelized Hashcodes. - Sahil Garg; Aram Galstyan; Irina Rish; Guillermo A. Cecchi; Shuyang Gao (CoRR, 2017)

Computing the structure of language for neuropsychiatric evaluation. - Guillermo A. Cecchi; Viatcheslav Gurev; Steve Heisig; Raquel Norel; Irina Rish; Samantha R. Schrecke (IBM J. Res. Dev., 2017)

Computational psychiatry: Advancing predictive modeling of neurodegeneration with neuroimaging of Huntington's disease. - Pablo Polosecki; Eduardo Castro; Andrew Wood; John H. Warner; Irina Rish; Guillermo A. Cecchi (IBM J. Res. Dev., 2017)

Holographic brain: Distributed versus local activation patterns in fMRI. - Irina Rish; Guillermo A. Cecchi (IBM J. Res. Dev., 2017)

Unsupervised Morphological Segmentation for Detecting Parkinson's Disease. - Elif Eyigöz; Pablo Polosecki; Adolfo M. García; Katharina Rogg; Juan Rafael Orozco-Arroyave; Sabine Skodda; Eugenia Hesse; Agustín Ibáñez; Guillermo A. Cecchi (AAAI Workshops, 2018)

Predicting Cognitive Impairments with a Mobile Application. - Elif Eyigöz; Guillermo A. Cecchi; Ravi Tejwani (ICAART (2), 2018)

Contextual Bandit with Adaptive Feature Extraction. - Baihan Lin; Djallel Bouneffouf 001; Guillermo A. Cecchi; Irina Rish (ICDM Workshops, 2018)

Dialogue Modeling Via Hash Functions. - Sahil Garg; Guillermo A. Cecchi; Irina Rish; Shuyang Gao; Greg Ver Steeg; Sarik Ghazarian; Palash Goyal; Aram Galstyan (LaCATODA@IJCAI, 2018)

Detection of Amyotrophic Lateral Sclerosis (ALS) via Acoustic Analysis. - Raquel Norel; Mary Pietrowicz; Carla Agurto; Shay Rishoni; Guillermo A. Cecchi (INTERSPEECH, 2018)

Predictive Linguistic Markers of Suicidality in Poets. - Carla Agurto; Pat Pataranutaporn; Elif K. Eyigöz; Gustavo Stolovitzky; Guillermo A. Cecchi (ICSC, 2018)

Adaptive Representation Selection in Contextual Bandit with Unlabeled History. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001; Irina Rish (CoRR, 2018)

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. - Germán Abrevaya; Aleksandr Y. Aravkin; Guillermo A. Cecchi; Irina Rish; Pablo Polosecki; Peng Zheng 002; Silvina Ponce Dawson (CoRR, 2018)

An entropic barriers diffusion theory of decision-making in multiple alternative tasks. - Diego Fernández Slezak; Mariano Sigman; Guillermo A. Cecchi (PLoS Comput. Biol., 2018)

Kernelized Hashcode Representations for Relation Extraction. - Sahil Garg; Aram Galstyan; Greg Ver Steeg; Irina Rish; Guillermo A. Cecchi; Shuyang Gao (AAAI, 2019)

Analyzing progression of motor and speech impairment in ALS. - Carla Agurto; Mary Pietrowicz; Elif K. Eyigöz; Elizabeth Mosmiller; Emily G. Baxi; Jeffrey D. Rothstein; Promit Roy; James D. Berry; Nicholas J. Maragakis; Omar Ahmad; Guillermo A. Cecchi; Raquel Norel (EMBC, 2019)

Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. - Sahil Garg; Aram Galstyan; Greg Ver Steeg; Guillermo A. Cecchi (EMNLP/IJCNLP (1), 2019)

Speech Markers for Clinical Assessment of Cocaine Users. - Carla Agurto; Raquel Norel; Mary Pietrowicz; Muhammad A. Parvaz; Sivan Kinreich; Keren Bachi; Guillermo A. Cecchi; Rita Z. Goldstein (ICASSP, 2019)

Dimensional Analysis of Laughter in Female Conversational Speech. - Mary Pietrowicz; Carla Agurto; Jonah Casebeer; Mark Hasegawa-Johnson; Karrie Karahalios; Guillermo A. Cecchi (ICASSP, 2019)

Efficient Data Representation by Selecting Prototypes with Importance Weights. - Karthik S. Gurumoorthy; Amit Dhurandhar; Guillermo A. Cecchi; Charu C. Aggarwal (ICDM, 2019)

Split Q Learning: Reinforcement Learning with Two-Stream Rewards. - Baihan Lin; Djallel Bouneffouf 001; Guillermo A. Cecchi (IJCAI, 2019)

A New Approach for Automating Analysis of Responses on Verbal Fluency Tests from Subjects At-Risk for Schizophrenia. - Mary Pietrowicz; Carla Agurto; Raquel Norel; Elif Eyigöz; Guillermo A. Cecchi; Zarina R. Bilgrami; Cheryl Corcoran (INTERSPEECH, 2019)

Predicting conversion to psychosis in clinical high risk patients using resting-state functional MRI features. - Jolie McDonnell; William Hord; Jenna M. Reinen; Pablo Polosecki; Irina Rish; Guillermo A. Cecchi (Biomedical Applications in Molecular, Structural, and Functional Imaging, 2019)

Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001; Jenna M. Reinen; Irina Rish (CoRR, 2019)

Nearly-Unsupervised Hashcode Representations for Relation Extraction. - Sahil Garg; Aram Galstyan; Greg Ver Steeg; Guillermo A. Cecchi (CoRR, 2019)

Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. - Sahil Garg; Irina Rish; Guillermo A. Cecchi; Palash Goyal; Sarik Ghazarian; Shuyang Gao; Greg Ver Steeg; Aram Galstyan (AAAI, 2020)

Evaluating the utility of a picture description task for monitoring progression of ALS at home. - Carla Agurto; Guillermo A. Cecchi; Mary Pietrowicz; Divya Ramamoorthy; Lorin Wilde; Elizabeth Mosmiller; Emily G. Baxi; Nicholas J. Maragakis; James D. Berry; Ernest Fraenkel; Jeffrey D. Rothstein; Raquel Norel (AMIA, 2020)

Cloud-Native Language-Based Analysis for Neurodegenerative Assessment. - Sundar Saranathan; Piyush Madan; Carla Agurto; Elif Eyigöz; Lauren Mitchell; Shilpa Mahatma; Guillermo A. Cecchi (AMIA, 2020)

A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001; Jenna M. Reinen; Irina Rish (AAMAS, 2020)

Analyzing acoustic and prosodic fluctuations in free speech to predict psychosis onset in high-risk youths. - Carla Agurto; Mary Pietrowicz; Raquel Norel; Elif K. Eyigöz; Emma Stanislawski; Guillermo A. Cecchi; Cheryl Corcoran (EMBC, 2020)

Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001; Jenna M. Reinen; Irina Rish (HBAI@IJCAI, 2020)

Dependency Analysis of Spoken Language for Assessment of Neurological Disorders. - Elif Eyigöz; Mary Pietrowicz; Carla Agurto; Juan Rafael Orozco-Arroyave; Adolfo M. García; Sabine Skodda; Jan Rusz; Elmar Nöth; Guillermo A. Cecchi (RaPID@LREC, 2020)

Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001; Jenna M. Reinen; Irina Rish (CoRR, 2020)

Predicting Human Decision Making in Psychological Tasks with Recurrent Neural Networks. - Baihan Lin; Djallel Bouneffouf 001; Guillermo A. Cecchi (CoRR, 2020)

Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. - Germán Abrevaya; Guillaume Dumas; Aleksandr Y. Aravkin; Peng Zheng 002; Jean-Christophe Gagnon-Audet; James R. Kozloski; Pablo Polosecki; Guillaume Lajoie; David D. Cox; Silvina Ponce Dawson; Guillermo A. Cecchi; Irina Rish (Neural Comput., 2021)

ALS community pressing issues: lessons from a survey. - Aria Anvar; James D. Berry; Ernest Fraenkel; Indu Navar; Guillermo A. Cecchi; Raquel Norel (AMIA, 2022)

Definition and clinical validation of Pain Patient States from high-dimensional mobile data: application to a chronic pain cohort. - Jenna M. Reinen; Carla Agurto; Guillermo A. Cecchi; Jeffrey L. Rogers; NAVITAS / ENVISION Studies Physician Author Group; Boston Scientific Research Scientists Consortium (ICDH, 2022)

Predicting Human Decision Making with LSTM. - Baihan Lin; Djallel Bouneffouf 001; Guillermo A. Cecchi (IJCNN, 2022)

Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior. - Baihan Lin; Djallel Bouneffouf 001; Guillermo A. Cecchi (PRICAI (3), 2022)

Deep Annotation of Therapeutic Working Alliance in Psychotherapy. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001 (CoRR, 2022)

Neural Topic Modeling of Psychotherapy Sessions. - Baihan Lin; Djallel Bouneffouf 001; Guillermo A. Cecchi; Ravi Tejwani (CoRR, 2022)

PainPoints: A Framework for Language-based Detection of Chronic Pain and Expert-Collaborative Text-Summarization. - Shreyas Fadnavis; Amit Dhurandhar; Raquel Norel; Jenna M. Reinen; Carla Agurto; Erica Secchettin; Vittorio Schweiger; Giovanni Perini; Guillermo A. Cecchi (CoRR, 2022)

Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data. - Divya Ramamoorthy; Kristen Severson; Soumya Ghosh; Karen Sachs; Emily G. Baxi; Alyssa N. Coyne; Elizabeth Mosmiller; Lindsey Hayes; Aianna Cerezo; Omar Ahmad; Promit Roy; Steven Zeiler; et al. (Nat. Comput. Sci., 2022)

Remote Inference of Cognitive Scores in ALS Patients Using a Picture Description. - Carla Agurto; Guillermo A. Cecchi; Bo Wen; Ernest Fraenkel; James D. Berry; Indu Navar; Raquel Norel (ICDH, 2023)

The Impact of COVID-19 on Chronic Pain: Multidimensional Clustering Reveals Deep Insights into Spinal Cord Stimulation Patients. - Sara E. Berger; Carla Agurto; Guillermo A. Cecchi; Elif Eyigöz; Brad Hershey; Kristen Lechleiter; Dat Huynh; Matt McDonald; Jeffrey L. Rogers (ICDH, 2023)

SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001 (IJCAI, 2023)

Helping Therapists with NLP-Annotated Recommendation 17-24. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001 (IUI Workshops, 2023)

Information theoretic clustering via divergence maximization among clusters. - Sahil Garg; Mina Dalirrooyfard; Anderson Schneider; Yeshaya Adler; Yuriy Nevmyvaka; Yu Chen; Fengpei Li; Guillermo A. Cecchi (UAI, 2023)

Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001 (WWW (Companion Volume), 2023)

TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts. - Baihan Lin; Stefan Zecevic; Djallel Bouneffouf 001; Guillermo A. Cecchi (CoRR, 2023)

Towards Healthy AI: Large Language Models Need Therapists Too. - Baihan Lin; Djallel Bouneffouf 001; Guillermo A. Cecchi; Kush R. Varshney (CoRR, 2023)

GOKU-UI: Ubiquitous Inference through Attention and Multiple Shooting for Continuous-time Generative Models. - Germán Abrevaya; Mahta Ramezanian-Panahi; Jean-Christophe Gagnon-Audet; Irina Rish; Pablo Polosecki; Silvina Ponce Dawson; Guillermo A. Cecchi; Guillaume Dumas (CoRR, 2023)

The Impact of COVID-19 on Chronic Pain: Multidimensional Clustering Reveals Deep Insights into Spinal Cord Stimulation Patients. - Sara E. Berger; Carla Agurto; Guillermo A. Cecchi; Elif Eyigöz; Brad Hershey; Kristen Lechleiter; NAVITAS / ENVISION Studies Physician Author Group; Dat Huynh; Matt McDonald; Jeffrey L. Rogers (CoRR, 2023)

Working Alliance Transformer for Psychotherapy Dialogue Classification. - Baihan Lin; Guillermo A. Cecchi; Djallel Bouneffouf 001 (ClinicalNLP@NAACL, 2024)

COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modeling. - Baihan Lin; Djallel Bouneffouf 001; Yulia Landa; Rachel Jespersen; Cheryl Corcoran; Guillermo A. Cecchi (CoRR, 2024)

Deep Generative Sampling in the Dual Divergence Space: A Data-efficient & Interpretative Approach for Generative AI. - Sahil Garg; Anderson Schneider; Anant Raj; Kashif Rasul; Yuriy Nevmyvaka; Sneihil Gopal; Amit Dhurandhar; Guillermo A. Cecchi; Irina Rish (CoRR, 2024)

People over trust AI-generated medical responses and view them to be as valid as doctors, despite low accuracy. - Shruthi Shekar; Pat Pataranutaporn; Chethan Sarabu; Guillermo A. Cecchi; Pattie Maes (CoRR, 2024)

Effective Latent Differential Equation Models via Attention and Multiple Shooting. - Germán Abrevaya; Mahta Ramezanian-Panahi; Jean-Christophe Gagnon-Audet; Pablo Polosecki; Irina Rish; Silvina Ponce Dawson; Guillermo A. Cecchi; Guillaume Dumas (Trans. Mach. Learn. Res., 2024)

TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts (short paper). - Baihan Lin; Stefan Zecevic; Djallel Bouneffouf 001; Guillermo A. Cecchi (IUI Workshops, 2025)

Clinical assessment and interpretation of dysarthria in ALS using attention based deep learning AI models. - Michele Merler; Carla Agurto; Julian Peller; Esteban Roitberg; Alan Taitz; Marcos A. Trevisan; Indu Navar; James D. Berry; Ernest Fraenkel; Lyle W. Ostrow; Guillermo A. Cecchi; Raquel Norel (npj Digit. Medicine, 2025)