Francisco Pereira

Affiliations:
  • National Institute of Mental Health, Bethesda, MD, USA
  • Siemens Corporation, Princeton, NJ, USA (2011 - 2017)
  • Princeton University, Neuroscience Institute, Psychology Department, NJ, USA (2007 - 2011)
  • Carnegie Mellon University, Computer Science Department, Pittsburgh, PA, USA (PhD 2007)


According to our database1, Francisco Pereira authored at least 33 papers between 2000 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

Online presence:

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Bibliography

2025
More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Enhancing Infant Crying Detection with Gradient Boosting for Improved Emotional and Mental Health Diagnostics.
CoRR, 2024

Causal Inference in the Closed-Loop: Marginal Structural Models for Sequential Excursion Effects.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023
Interpretable factorization of clinical questionnaires to identify latent factors of psychopathology.
CoRR, 2023

2022
Testing for context-dependent changes in neural encoding in naturalistic experiments.
CoRR, 2022

VICE: Variational Interpretable Concept Embeddings.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Mental representations of objects reflect the ways in which we interact with them.
Proceedings of the 43rd Annual Meeting of the Cognitive Science Society, 2021

2020
A Deep Neural Network Tool for Automatic Segmentation of Human Body Parts in Natural Scenes.
CoRR, 2020

Understanding Object Affordances Through Verb Usage Patterns.
CoRR, 2020

Evaluating Adversarial Robustness for Deep Neural Network Interpretability using fMRI Decoding.
CoRR, 2020

2019
Imaging the spontaneous flow of thought: Distinct periods of cognition contribute to dynamic functional connectivity during rest.
NeuroImage, 2019

Knowing What You Know in Brain Segmentation Using Bayesian Deep Neural Networks.
Frontiers Neuroinformatics, 2019

Revealing interpretable object representations from human behavior.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Knowing what you know in brain segmentation using deep neural networks.
CoRR, 2018

Parallel Weight Consolidation: A Brain Segmentation Case Study.
CoRR, 2018

Semantic projection: recovering human knowledge of multiple, distinct object features from word embeddings.
CoRR, 2018

Distributed Weight Consolidation: A Brain Segmentation Case Study.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2013
Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments.
Artif. Intell., 2013

Creating Group-Level Functionally-Defined Atlases for Diagnostic Classification.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Simitar: Simplified Searching of Statistically Significant Similarity Structure.
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013

Simultaneous label fusion with vessel preserving for bone removal in CT angiography scans.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

2012
A systematic approach to extracting semantic information from functional MRI data.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Information mapping with pattern classifiers: A comparative study.
NeuroImage, 2011

A topographic latent source model for fMRI data.
NeuroImage, 2011

Classification of functional magnetic resonance imaging data using informative pattern features.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2009
Machine learning classifiers and fMRI: A tutorial overview.
NeuroImage, 2009

2008
Closed-form supervised dimensionality reduction with generalized linear models.
Proceedings of the Machine Learning, 2008

2006
The support vector decomposition machine.
Proceedings of the Machine Learning, 2006

2004
Learning to Decode Cognitive States from Brain Images.
Mach. Learn., 2004

Detecting Significant Multidimensional Spatial Clusters.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003
Classifying Instantaneous Cognitive States from fMRI Data.
Proceedings of the AMIA 2003, 2003

2001
Distinguishing Natural Language Processes on the Basis of fMRI-Measured Brain Activation.
Proceedings of the Principles of Data Mining and Knowledge Discovery, 2001

2000
Concise, intelligible, and approximate profiling of multiple classes.
Int. J. Hum. Comput. Stud., 2000


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