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ORCIDGuillermo A. Cecchi
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- affiliation: IBM Research, Yorktown Heights, NY, USA
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2020 – today
- 2024
[j17]Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Pablo Polosecki, Irina Rish, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas:
Effective Latent Differential Equation Models via Attention and Multiple Shooting. Trans. Mach. Learn. Res. 2024 (2024)- [c72]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf:
Working Alliance Transformer for Psychotherapy Dialogue Classification. ClinicalNLP@NAACL 2024: 64-69 - [i28]Baihan Lin, Djallel Bouneffouf, Yulia Landa, Rachel Jespersen, Cheryl Corcoran, Guillermo A. Cecchi:
COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modeling. CoRR abs/2402.14701 (2024) - [i27]Sahil Garg, Anderson Schneider, Anant Raj, Kashif Rasul, Yuriy Nevmyvaka, Sneihil Gopal, Amit Dhurandhar, Guillermo A. Cecchi, Irina Rish:
Deep Generative Sampling in the Dual Divergence Space: A Data-efficient & Interpretative Approach for Generative AI. CoRR abs/2404.07377 (2024) - [i26]Shruthi Shekar, Pat Pataranutaporn, Chethan Sarabu, Guillermo A. Cecchi, Pattie Maes:
People over trust AI-generated medical responses and view them to be as valid as doctors, despite low accuracy. CoRR abs/2408.15266 (2024) - 2023
- [c71]Carla Agurto, Guillermo A. Cecchi, Bo Wen, Ernest Fraenkel, James D. Berry, Indu Navar, Raquel Norel:
Remote Inference of Cognitive Scores in ALS Patients Using a Picture Description. ICDH 2023: 50-56 - [c70]Sara E. Berger
, Carla Agurto, Guillermo A. Cecchi, Elif Eyigöz, Brad Hershey, Kristen Lechleiter, Dat Huynh, Matt McDonald, Jeffrey L. Rogers:
The Impact of COVID-19 on Chronic Pain: Multidimensional Clustering Reveals Deep Insights into Spinal Cord Stimulation Patients. ICDH 2023: 91-99 - [c69]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf:
SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning. IJCAI 2023: 7149-7153 - [c68]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf:
Helping Therapists with NLP-Annotated Recommendation 17-24. IUI Workshops 2023: 17-24 - [c67]Sahil Garg, Mina Dalirrooyfard, Anderson Schneider, Yeshaya Adler, Yuriy Nevmyvaka, Yu Chen, Fengpei Li, Guillermo A. Cecchi:
Information theoretic clustering via divergence maximization among clusters. UAI 2023: 624-634 - [c66]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf:
Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics. WWW (Companion Volume) 2023: 932-939 - [i25]Baihan Lin, Stefan Zecevic, Djallel Bouneffouf, Guillermo A. Cecchi:
TherapyView: Visualizing Therapy Sessions with Temporal Topic Modeling and AI-Generated Arts. CoRR abs/2302.10845 (2023) - [i24]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf:
Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics. CoRR abs/2303.09601 (2023) - [i23]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Kush R. Varshney:
Towards Healthy AI: Large Language Models Need Therapists Too. CoRR abs/2304.00416 (2023) - [i22]Germán Abrevaya, Mahta Ramezanian-Panahi, Jean-Christophe Gagnon-Audet, Irina Rish, Pablo Polosecki, Silvina Ponce Dawson, Guillermo A. Cecchi, Guillaume Dumas:
GOKU-UI: Ubiquitous Inference through Attention and Multiple Shooting for Continuous-time Generative Models. CoRR abs/2307.05735 (2023) - [i21]Carla Agurto, Guillermo A. Cecchi, Bo Wen, Ernest Fraenkel, James D. Berry, Indu Navar, Raquel Norel:
Remote Inference of Cognitive Scores in ALS Patients Using a Picture Description. CoRR abs/2309.06989 (2023) - [i20]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:
The Impact of COVID-19 on Chronic Pain: Multidimensional Clustering Reveals Deep Insights into Spinal Cord Stimulation Patients. CoRR abs/2310.01390 (2023) - 2022
- [j16]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, John W. Krakauer, Jonathan Li, Aneesh Donde, Nhan Huynh, Miriam Adam, Brook T. Wassie, Alexander LeNail, Natasha Leanna Patel-Murray, Yogindra Raghav, Velina Kozareva, Stanislav Tsitkov, Tobias Ehrenberger, Julia A. Kaye, Leandro Lima, Stacia K. Wyman, Edward Vertudes, Naufa Amirani, Krishna Raja, Reuben Thomas, Ryan G. Lim, Ricardo Miramontes, Jie Wu, Vineet Vaibhav, Andrea Matlock, Vidya Venkatraman, Ronald Holewenski, Niveda Sundararaman, Rakhi Pandey, Danica-Mae Manalo, Aaron Frank, Loren Ornelas, Lindsey Panther, Emilda Gomez, Erick Galvez, Daniel Pérez, Imara Meepe, Susan Lei, Louis Pinedo, Chunyan Liu, Ruby Moran, Dhruv Sareen, Barry Landin, Carla Agurto, Guillermo A. Cecchi, Raquel Norel, Sara Thrower, Sarah Luppino, Alanna Farrar, Lindsay Pothier, Hong Yu, Ervin Sinani, Prasha Vigneswaran, Alexander V. Sherman, S. Michelle Farr, Berhan Mandefro, Hannah Trost, Maria G. Banuelos, Veronica Garcia, Michael Workman, Richie Ho, Robert Baloh, Jennifer Roggenbuck, Matthew B. Harms, Carolyn Prina, Sarah Heintzman, Stephen Kolb, Jennifer Stocksdale, Keona Wang, Todd Morgan, Daragh Heitzman, Arish Jamil, Jennifer Jockel-Balsarotti, Elizabeth Karanja, Jesse Markway, Molly McCallum, Tim Miller, Ben Joslin, Deniz Alibazoglu, Senda Ajroud-Driss, Jay C. Beavers, Mary Bellard, Elizabeth Bruce, Nicholas J. Maragakis, Merit E. Cudkowicz, James D. Berry, Terri Thompson, Steven Finkbeiner, Leslie M. Thompson, Jennifer E. Van Eyk, Clive N. Svendsen, Jeffrey D. Rothstein, Jonathan D. Glass, Christina N. Fournier, Alexander Sherman, Christian Lunetta, David Walk, Ghazala Hayat, James Wymer, Kelly Gwathmey, Nicholas Olney, Terry Heiman-Patterson, Ximena Arcila-Londono, Kenneth Faulconer, Ervin Sanani, Alex Berger, Julia Mirochnick, Todd M. Herrington, Kenney Ng, Ernest Fraenkel:
Identifying patterns in amyotrophic lateral sclerosis progression from sparse longitudinal data. Nat. Comput. Sci. 2(9): 605-616 (2022) - [c65]Aria Anvar, James D. Berry, Ernest Fraenkel, Indu Navar, Guillermo A. Cecchi, Raquel Norel:
ALS community pressing issues: lessons from a survey. AMIA 2022 - [c64]Jenna M. Reinen, Carla Agurto, Guillermo A. Cecchi, Jeffrey L. Rogers, NAVITAS / ENVISION Studies Physician Author Group, Boston Scientific Research Scientists Consortium:
Definition and clinical validation of Pain Patient States from high-dimensional mobile data: application to a chronic pain cohort. ICDH 2022: 47-53 - [c63]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi:
Predicting Human Decision Making with LSTM. IJCNN 2022: 1-8 - [c62]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi:
Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior. PRICAI (3) 2022: 134-147 - [i19]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf:
Deep Annotation of Therapeutic Working Alliance in Psychotherapy. CoRR abs/2204.05522 (2022) - [i18]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Ravi Tejwani:
Neural Topic Modeling of Psychotherapy Sessions. CoRR abs/2204.10189 (2022) - [i17]Shreyas Fadnavis, Amit Dhurandhar, Raquel Norel, Jenna M. Reinen, Carla Agurto, Erica Secchettin, Vittorio Schweiger, Giovanni Perini, Guillermo A. Cecchi:
PainPoints: A Framework for Language-based Detection of Chronic Pain and Expert-Collaborative Text-Summarization. CoRR abs/2209.09814 (2022) - [i16]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf:
Working Alliance Transformer for Psychotherapy Dialogue Classification. CoRR abs/2210.15603 (2022) - 2021
- [j15]Germán Abrevaya, Guillaume Dumas, Aleksandr Y. Aravkin, Peng Zheng, Jean-Christophe Gagnon-Audet, James R. Kozloski, Pablo Polosecki, Guillaume Lajoie, David D. Cox, Silvina Ponce Dawson, Guillermo A. Cecchi, Irina Rish:
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks. Neural Comput. 33(8): 2087-2127 (2021) - 2020
- [c61]Sahil Garg, Irina Rish, Guillermo A. Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan:
Modeling Dialogues with Hashcode Representations: A Nonparametric Approach. AAAI 2020: 3970-3979 - [c60]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:
Evaluating the utility of a picture description task for monitoring progression of ALS at home. AMIA 2020 - [c59]Sundar Saranathan, Piyush Madan, Carla Agurto, Elif Eyigöz, Lauren Mitchell, Shilpa Mahatma, Guillermo A. Cecchi:
Cloud-Native Language-Based Analysis for Neurodegenerative Assessment. AMIA 2020 - [c58]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish:
A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry. AAMAS 2020: 744-752 - [c57]Carla Agurto, Mary Pietrowicz, Raquel Norel, Elif K. Eyigöz, Emma Stanislawski, Guillermo A. Cecchi, Cheryl Corcoran:
Analyzing acoustic and prosodic fluctuations in free speech to predict psychosis onset in high-risk youths. EMBC 2020: 5575-5579 - [c56]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish:
Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. HBAI@IJCAI 2020: 14-33 - [c55]Elif Eyigöz, Mary Pietrowicz, Carla Agurto, Juan Rafael Orozco-Arroyave, Adolfo M. García, Sabine Skodda, Jan Rusz, Elmar Nöth, Guillermo A. Cecchi:
Dependency Analysis of Spoken Language for Assessment of Neurological Disorders. RaPID@LREC 2020 - [i15]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish:
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL. CoRR abs/2005.04544 (2020) - [i14]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi:
Online Learning in Iterated Prisoner's Dilemma to Mimic Human Behavior. CoRR abs/2006.06580 (2020) - [i13]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi:
Predicting Human Decision Making in Psychological Tasks with Recurrent Neural Networks. CoRR abs/2010.11413 (2020)
2010 – 2019
- 2019
- [c54]Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo A. Cecchi, Shuyang Gao:
Kernelized Hashcode Representations for Relation Extraction. AAAI 2019: 6431-6440 - [c53]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:
Analyzing progression of motor and speech impairment in ALS. EMBC 2019: 6097-6102 - [c52]Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi:
Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction. EMNLP/IJCNLP (1) 2019: 4024-4034 - [c51]Carla Agurto, Raquel Norel, Mary Pietrowicz, Muhammad A. Parvaz, Sivan Kinreich, Keren Bachi, Guillermo A. Cecchi, Rita Z. Goldstein:
Speech Markers for Clinical Assessment of Cocaine Users. ICASSP 2019: 6391-6394 - [c50]Mary Pietrowicz, Carla Agurto, Jonah Casebeer, Mark Hasegawa-Johnson, Karrie Karahalios, Guillermo A. Cecchi:
Dimensional Analysis of Laughter in Female Conversational Speech. ICASSP 2019: 6600-6604 - [c49]Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo A. Cecchi, Charu C. Aggarwal:
Efficient Data Representation by Selecting Prototypes with Importance Weights. ICDM 2019: 260-269 - [c48]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi:
Split Q Learning: Reinforcement Learning with Two-Stream Rewards. IJCAI 2019: 6448-6449 - [c47]Mary Pietrowicz, Carla Agurto, Raquel Norel, Elif Eyigöz, Guillermo A. Cecchi, Zarina R. Bilgrami, Cheryl Corcoran:
A New Approach for Automating Analysis of Responses on Verbal Fluency Tests from Subjects At-Risk for Schizophrenia. INTERSPEECH 2019: 3028-3032 - [c46]Jolie McDonnell, William Hord, Jenna M. Reinen, Pablo Polosecki, Irina Rish, Guillermo A. Cecchi:
Predicting conversion to psychosis in clinical high risk patients using resting-state functional MRI features. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2019: 109532A - [i12]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna M. Reinen, Irina Rish:
Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders. CoRR abs/1906.11286 (2019) - [i11]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi:
Split Q Learning: Reinforcement Learning with Two-Stream Rewards. CoRR abs/1906.12350 (2019) - [i10]Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A. Cecchi:
Nearly-Unsupervised Hashcode Representations for Relation Extraction. CoRR abs/1909.03881 (2019) - 2018
- [j14]Diego Fernández Slezak, Mariano Sigman, Guillermo A. Cecchi:
An entropic barriers diffusion theory of decision-making in multiple alternative tasks. PLoS Comput. Biol. 14(3) (2018) - [c45]Elif Eyigöz, Pablo Polosecki, Adolfo M. García, Katharina Rogg, Juan Rafael Orozco-Arroyave, Sabine Skodda, Eugenia Hesse, Agustín Ibáñez, Guillermo A. Cecchi:
Unsupervised Morphological Segmentation for Detecting Parkinson's Disease. AAAI Workshops 2018: 126-131 - [c44]Elif Eyigöz, Guillermo A. Cecchi, Ravi Tejwani:
Predicting Cognitive Impairments with a Mobile Application. ICAART (2) 2018: 683-692 - [c43]Baihan Lin, Djallel Bouneffouf, Guillermo A. Cecchi, Irina Rish:
Contextual Bandit with Adaptive Feature Extraction. ICDM Workshops 2018: 937-944 - [c42]Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan:
Dialogue Modeling Via Hash Functions. LaCATODA@IJCAI 2018: 24-36 - [c41]Raquel Norel, Mary Pietrowicz, Carla Agurto, Shay Rishoni, Guillermo A. Cecchi:
Detection of Amyotrophic Lateral Sclerosis (ALS) via Acoustic Analysis. INTERSPEECH 2018: 377-381 - [c40]Carla Agurto, Pat Pataranutaporn, Elif K. Eyigöz, Gustavo Stolovitzky, Guillermo A. Cecchi:
Predictive Linguistic Markers of Suicidality in Poets. ICSC 2018: 282-285 - [i9]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Irina Rish:
Adaptive Representation Selection in Contextual Bandit with Unlabeled History. CoRR abs/1802.00981 (2018) - [i8]Germán Abrevaya, Aleksandr Y. Aravkin, Guillermo A. Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Ponce Dawson:
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. CoRR abs/1805.09874 (2018) - 2017
- [j13]Guillermo A. Cecchi, Viatcheslav Gurev, Steve Heisig, Raquel Norel, Irina Rish, Samantha R. Schrecke:
Computing the structure of language for neuropsychiatric evaluation. IBM J. Res. Dev. 61(2/3): 1:1-1:10 (2017) - [j12]Irina Rish, Guillermo A. Cecchi:
Holographic brain: Distributed versus local activation patterns in fMRI. IBM J. Res. Dev. 61(2/3): 3:1-3:9 (2017) - [j11]Pablo Polosecki, Eduardo Castro, Andrew Wood, John H. Warner, Irina Rish, Guillermo A. Cecchi:
Computational psychiatry: Advancing predictive modeling of neurodegeneration with neuroimaging of Huntington's disease. IBM J. Res. Dev. 61(2/3): 4:1-4:10 (2017) - [c39]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi:
Bandit Models of Human Behavior: Reward Processing in Mental Disorders. AGI 2017: 237-248 - [c38]E. Dario Gutiérrez, Guillermo A. Cecchi, Cheryl Corcoran, Philip R. Corlett:
Using Automated Metaphor Identification to Aid in Detection and Prediction of First-Episode Schizophrenia. EMNLP 2017: 2923-2930 - [c37]Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano:
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. ICLR (Workshop) 2017 - [c36]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphaël Féraud:
Context Attentive Bandits: Contextual Bandit with Restricted Context. IJCAI 2017: 1468-1475 - [c35]Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano:
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. IJCAI 2017: 1696-1702 - [c34]Carla Agurto, Raquel Norel, Rachel Ostrand, Gillinder Bedi, Harriet de Wit, Matthew J. Baggott, Matthew G. Kirkpatrick, Margaret Wardle, Guillermo A. Cecchi:
Phonological Markers of Oxytocin and MDMA Ingestion. INTERSPEECH 2017: 3142-3146 - [c33]Mina Gheiratmand, Irina Rish, Guillermo A. Cecchi, Matthew R. G. Brown, Russell Greiner, Pouya Bashivan, Pablo Polosecki, Serdar M. Dursun:
Learning discriminative functional network features of schizophrenia. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2017: 101371A - [i7]Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano:
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. CoRR abs/1701.06106 (2017) - [i6]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphaël Féraud:
Context Attentive Bandits: Contextual Bandit with Restricted Context. CoRR abs/1705.03821 (2017) - [i5]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi:
Bandit Models of Human Behavior: Reward Processing in Mental Disorders. CoRR abs/1706.02897 (2017) - [i4]Karthik S. Gurumoorthy, Amit Dhurandhar, Guillermo A. Cecchi:
ProtoDash: Fast Interpretable Prototype Selection. CoRR abs/1707.01212 (2017) - [i3]Sahil Garg, Aram Galstyan, Irina Rish, Guillermo A. Cecchi, Shuyang Gao:
Efficient Representation for Natural Language Processing via Kernelized Hashcodes. CoRR abs/1711.04044 (2017) - 2016
- [c32]Irina Rish, Pouya Bashivan, Guillermo A. Cecchi, Rita Z. Goldstein:
Evaluating effects of methylphenidate on brain activity in cocaine addiction: a machine-learning approach. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2016: 97880O - [e1]Irina Rish, Georg Langs, Leila Wehbe, Guillermo A. Cecchi, Kai-min Kevin Chang, Brian Murphy:
Machine Learning and Interpretation in Neuroimaging - 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers. Lecture Notes in Computer Science 9444, Springer 2016, ISBN 978-3-319-45173-2 [contents] - [i2]Facundo Carrillo, Natalia Mota, Mauro Copelli, Sidarta Ribeiro, Mariano Sigman, Guillermo A. Cecchi, Diego Fernández Slezak:
Emotional Intensity analysis in Bipolar subjects. CoRR abs/1606.02231 (2016) - [i1]Natalia Bezerra Mota, Sylvia Pinheiro, Mariano Sigman, Diego Fernández Slezak, Guillermo A. Cecchi, Mauro Copelli, Sidarta Ribeiro:
The ontogeny of discourse structure mimics the development of literature. CoRR abs/1612.09268 (2016) - 2015
- [j10]Facundo Carrillo, Guillermo A. Cecchi, Mariano Sigman, Diego Fernández Slezak:
Fast Distributed Dynamics of Semantic Networks via Social Media. Comput. Intell. Neurosci. 2015: 712835:1-712835:9 (2015) - 2014
- [j9]Pablo Meyer, Guillermo A. Cecchi, Gustavo Stolovitzky:
Spatial localization of the first and last enzymes effectively connects active metabolic pathways in bacteria. BMC Syst. Biol. 8: 131 (2014) - [c31]Facundo Carrillo, Natalia Mota, Mauro Copelli, Sidarta Ribeiro, Mariano Sigman, Guillermo A. Cecchi, Diego Fernández Slezak:
Automated Speech Analysis for Psychosis Evaluation. MLINI@NIPS 2014: 31-39 - 2013
- [j8]Alex T. Baria, A. Mansour, Lejian Huang, Marwan N. Baliki, Guillermo A. Cecchi, M.-Marsel Mesulam, Apkar Vania Apkarian:
Linking human brain local activity fluctuations to structural and functional network architectures. NeuroImage 73: 144-155 (2013) - [c30]A. Ravishankar Rao, Guillermo A. Cecchi:
Multi-sensory integration using sparse spatio-temporal encoding. IJCNN 2013: 1-8 - [c29]A. Ravishankar Rao, Guillermo A. Cecchi:
Capacity limits in oscillatory networks: Implications for sensory coding. IJCNN 2013: 1-8 - 2012
- [j7]Guillermo A. Cecchi, Lejian Huang, Javeria Ali Hashmi, Marwan N. Baliki, María V. Centeno, Irina Rish, Apkar Vania Apkarian:
Predictive Dynamics of Human Pain Perception. PLoS Comput. Biol. 8(10) (2012) - [c28]Irina Rish, Guillermo A. Cecchi, Kyle Heuton, Marwan N. Baliki, Apkar Vania Apkarian:
Sparse regression analysis of task-relevant information distribution in the brain. Medical Imaging: Image Processing 2012: 831412 - [c27]Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo A. Cecchi:
Variable Selection for Gaussian Graphical Models. AISTATS 2012: 538-546 - 2011
- [j6]Rahul Garg, Guillermo A. Cecchi, A. Ravishankar Rao:
Full-brain auto-regressive modeling (FARM) using fMRI. NeuroImage 58(2): 416-441 (2011) - [c26]A. Ravishankar Rao, Guillermo A. Cecchi:
The effects of feedback and lateral connections on perceptual processing: A study using oscillatory networks. IJCNN 2011: 1177-1184 - [c25]A. Ravishankar Rao, Rahul Garg, Guillermo A. Cecchi:
A spatio-temporal support vector machine searchlight for fMRI analysis. ISBI 2011: 1023-1026 - [c24]Rahul Garg, Guillermo A. Cecchi, A. Ravishankar Rao:
Brain as a self-predictor: Sparse full-brain auto-regressive modeling in fMRI. ISBI 2011: 1581-1584 - [c23]A. Ravishankar Rao, Rajesh Bordawekar, Guillermo A. Cecchi:
Fast computation of functional networks from fMRI activity: a multi-platform comparison. Medical Imaging: Image Processing 2011: 79624L - 2010
- [j5]A. Ravishankar Rao, Guillermo A. Cecchi:
An objective function utilizing complex sparsity for efficient segmentation in multi-layer oscillatory networks. Int. J. Intell. Comput. Cybern. 3(2): 173-206 (2010) - [c22]Irina Rish, Guillermo A. Cecchi, Marwan N. Baliki, Apkar Vania Apkarian:
Sparse Regression Models of Pain Perception. Brain Informatics 2010: 212-223 - [c21]A. Ravishankar Rao, Guillermo A. Cecchi:
Investigating the variation of orientation tuning in a computational model of the visual cortex. IJCNN 2010: 1-8 - [c20]Iván Raskovsky, Diego Fernández Slezak, Carlos Diuk, Guillermo A. Cecchi:
The emergence of the modern concept of introspection: a quantitative linguistic analysis. NAACL (Young Investigators Workshop) 2010: 68-75
2000 – 2009
- 2009
- [j4]Melissa K. Carroll, Guillermo A. Cecchi, Irina Rish, Rahul Garg, A. Ravishankar Rao:
Prediction and interpretation of distributed neural activity with sparse models. NeuroImage 44(1): 112-122 (2009) - [c19]A. Ravishankar Rao, Guillermo A. Cecchi:
Self-Organizing Map Simulations Confirm Similarity of Spatial Correlation Structure in Natural Images and Cortical Representations. ICANN (1) 2009: 587-597 - [c18]A. Ravishankar Rao, Guillermo A. Cecchi:
An optimization approach to understanding structure-function relationships in the visual cortex. IJCNN 2009: 2603-2610 - [c17]Guillermo A. Cecchi, Rahul Garg, A. Ravishankar Rao:
A Cluster Overlap Measure for Comparison of Activations in fMRI Studies. MICCAI (1) 2009: 1018-1025 - [c16]Guillermo A. Cecchi, Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-Laure Paillère-Martinot, Catherine Martelli, Jean-Luc Martinot, Jean-Baptiste Poline:
Discriminative Network Models of Schizophrenia. NIPS 2009: 252-260 - 2008
- [j3]Youping Xiao, Ravi Rao, Guillermo A. Cecchi, Ehud Kaplan:
Improved mapping of information distribution across the cortical surface with the support vector machine. Neural Networks 21(2-3): 341-348 (2008) - [j2]A. Ravishankar Rao, Guillermo A. Cecchi, Charles C. Peck, James R. Kozloski:
Unsupervised Segmentation With Dynamical Units. IEEE Trans. Neural Networks 19(1): 168-182 (2008) - [c15]Guillermo A. Cecchi, A. Ravishankar Rao, Youping Xiao, Ehud Kaplan:
Statistics of natural scenes and the cortical representation of color. Human Vision and Electronic Imaging 2008: 680607 - [c14]A. Ravishankar Rao, Guillermo A. Cecchi:
Spatio-temporal Dynamics during Perceptual Processing in an Oscillatory Neural Network. ICANN (2) 2008: 685-694 - [c13]Irina Rish, Genady Grabarnik, Guillermo A. Cecchi, Francisco Pereira, Geoffrey J. Gordon:
Closed-form supervised dimensionality reduction with generalized linear models. ICML 2008: 832-839 - [c12]A. Ravishankar Rao, Guillermo A. Cecchi, Charles C. Peck, James R. Kozloski:
Efficient segmentation in multi-layer oscillatory networks. IJCNN 2008: 2966-2973 - [c11]Guillermo A. Cecchi, Rahul Garg, A. Ravishankar Rao:
Inferring brain dynamics using granger causality on fMRI data. ISBI 2008: 604-607 - 2007
- [c10]Charles C. Peck, James R. Kozloski, Guillermo A. Cecchi, Sean L. Hill, Felix Schürmann, Henry Markram, Ravi Rao:
Network-Related Challenges and Insights from Neuroscience. BIOWIRE 2007: 67-78 - [c9]Youping Xiao, Ravi Rao, Guillermo A. Cecchi, Ehud Kaplan:
Cortical representation of information about visual attributes: one network or many? IJCNN 2007: 1785-1789 - [c8]James R. Kozloski, Guillermo A. Cecchi, Charles C. Peck, A. Ravishankar Rao:
Topographic Infomax in a Neural Multigrid. ISNN (2) 2007: 500-509 - [c7]A. Ravishankar Rao, Guillermo A. Cecchi, Charles C. Peck, James R. Kozloski:
Emergence of Topographic Cortical Maps in a Parameterless Local Competition Network. ISNN (2) 2007: 552-561 - 2006
- [c6]Yuan Liu, Guillermo A. Cecchi, A. Ravishankar Rao, James R. Kozloski, Charles C. Peck:
Inference and segmentation in cortical processing. Human Vision and Electronic Imaging 2006: 60570Y - [c5]A. Ravishankar Rao, Guillermo A. Cecchi, Charles C. Peck, James R. Kozloski:
An optimization approach to achieve unsupervised segmentation and binding in a dynamical network. IJCNN 2006: 4159-4166 - 2005
- [c4]A. Ravishankar Rao, Guillermo A. Cecchi, Charles C. Peck, James R. Kozloski:
A model of the formation of a self-organized cortical representation of color. Human Vision and Electronic Imaging 2005: 17-26 - [c3]A. Ravishankar Rao, Guillermo A. Cecchi, Charles C. Peck, James R. Kozloski:
Evaluation of the Effect of Input Stimuli on the Quality of Orientation Maps Produced Through Self Organization. SCIA 2005: 810-820 - 2003
- [c2]Charles C. Peck, James R. Kozloski, A. Ravishankar Rao, Guillermo A. Cecchi:
Simulation Infrastructure for Modeling Large Scale Neural Systems. International Conference on Computational Science 2003: 1127-1136 - 2001
- [j1]Guillermo A. Cecchi, Leopoldo T. Petreanu, Arturo Alvarez-Buylla, Marcelo O. Magnasco:
Unsupervised Learning and Adaptation in a Model of Adult Neurogenesis. J. Comput. Neurosci. 11(2): 175-182 (2001)
1990 – 1999
- 1996
- [c1]Peter D. Kaplan, Guillermo A. Cecchi, Albert Libchaber:
DNA based molecular computation: Template-template interactions in PCR. DNA Based Computers 1996: 97-104
Coauthor Index
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