no code implementations • 17 Nov 2022 • Yenho Chen, Carl W. Harris, Xiaoyu Ma, Zheng Li, Francisco Pereira, Charles Y. Zheng
We propose a decoding-based approach to detect context effects on neural codes in longitudinal neural recording data.
no code implementations • 9 Aug 2022 • Niklas Petersen, Filipe Rodrigues, Francisco Pereira
We present a vector-space model for encoding rare temporal conditions, that allows coherent representation learning across different temporal conditions.
1 code implementation • 2 May 2022 • Lukas Muttenthaler, Charles Y. Zheng, Patrick McClure, Robert A. Vandermeulen, Martin N. Hebart, Francisco Pereira
This paper introduces Variational Interpretable Concept Embeddings (VICE), an approximate Bayesian method for embedding object concepts in a vector space using data collected from humans in a triplet odd-one-out task.
no code implementations • 1 Jan 2021 • Ka Chun Lam, Francisco Pereira, Maryam Vaziri-Pashkam, Kristin Woodard, Emalie McMahon
Finally, we show that the dimensions can be used to predict a state-of-the-art mental representation of objects, derived purely from human judgements of object similarity.
1 code implementation • 8 Sep 2020 • Patrick McClure, Gabrielle Reimann, Michal Ramot, Francisco Pereira
This short article describes a deep neural network trained to perform automatic segmentation of human body parts in natural scenes.
no code implementations • 22 Jun 2020 • Ka Chun Lam, Francisco Pereira, Maryam Vaziri-Pashkam, Kristin Woodard, Emalie McMahon
In order to interact with objects in our environment, humans rely on an understanding of the actions that can be performed on them, as well as their properties.
1 code implementation • 23 Apr 2020 • Patrick McClure, Dustin Moraczewski, Ka Chun Lam, Adam Thomas, Francisco Pereira
We introduce two quantitative evaluation procedures for saliency map methods in fMRI, applicable whenever a DNN or linear model is being trained to decode some information from imaging data.
no code implementations • 10 Jun 2019 • Filipe Rodrigues, Nicola Ortelli, Michel Bierlaire, Francisco Pereira
Specifying utility functions is a key step towards applying the discrete choice framework for understanding the behaviour processes that govern user choices.
no code implementations • ICLR 2019 • Charles Y. Zheng, Francisco Pereira, Chris I. Baker, Martin N. Hebart
To study how mental object representations are related to behavior, we estimated sparse, non-negative representations of objects using human behavioral judgments on images representative of 1, 854 object categories.
1 code implementation • 3 Dec 2018 • Patrick McClure, Nao Rho, John A. Lee, Jakub R. Kaczmarzyk, Charles Zheng, Satrajit S. Ghosh, Dylan Nielson, Adam G. Thomas, Peter Bandettini, Francisco Pereira
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours.
no code implementations • 17 Aug 2018 • Filipe Rodrigues, Mariana Lourenço, Bernardete Ribeiro, Francisco Pereira
The growing need to analyze large collections of documents has led to great developments in topic modeling.
no code implementations • 16 Aug 2018 • Filipe Rodrigues, Ioulia Markou, Francisco Pereira
Accurate time-series forecasting is vital for numerous areas of application such as transportation, energy, finance, economics, etc.
no code implementations • NeurIPS 2018 • Patrick McClure, Charles Y. Zheng, Jakub R. Kaczmarzyk, John A. Lee, Satrajit S. Ghosh, Dylan Nielson, Peter Bandettini, Francisco Pereira
Collecting the large datasets needed to train deep neural networks can be very difficult, particularly for the many applications for which sharing and pooling data is complicated by practical, ethical, or legal concerns.
no code implementations • 5 Feb 2018 • Gabriel Grand, Idan Asher Blank, Francisco Pereira, Evelina Fedorenko
Because related words appear in similar contexts, such spaces - called "word embeddings" - can be learned from patterns of lexical co-occurrences in natural language.
3 code implementations • 6 Sep 2017 • Filipe Rodrigues, Francisco Pereira
Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the state-of-the-art in various domains.
no code implementations • NeurIPS 2012 • Francisco Pereira, Matthew Botvinick
This paper introduces a novel classification method for functional magnetic resonance imaging datasets with tens of classes.