Search Results for author: Xiangrui Li

Found 12 papers, 2 papers with code

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

no code implementations11 Sep 2023 Russell A. Poldrack, Christopher J. Markiewicz, Stefan Appelhoff, Yoni K. Ashar, Tibor Auer, Sylvain Baillet, Shashank Bansal, Leandro Beltrachini, Christian G. Benar, Giacomo Bertazzoli, Suyash Bhogawar, Ross W. Blair, Marta Bortoletto, Mathieu Boudreau, Teon L. Brooks, Vince D. Calhoun, Filippo Maria Castelli, Patricia Clement, Alexander L Cohen, Julien Cohen-Adad, Sasha D'Ambrosio, Gilles de Hollander, María de la iglesia-Vayá, Alejandro de la Vega, Arnaud Delorme, Orrin Devinsky, Dejan Draschkow, Eugene Paul Duff, Elizabeth Dupre, Eric Earl, Oscar Esteban, Franklin W. Feingold, Guillaume Flandin, anthony galassi, Giuseppe Gallitto, Melanie Ganz, Rémi Gau, James Gholam, Satrajit S. Ghosh, Alessio Giacomel, Ashley G Gillman, Padraig Gleeson, Alexandre Gramfort, Samuel Guay, Giacomo Guidali, Yaroslav O. Halchenko, Daniel A. Handwerker, Nell Hardcastle, Peer Herholz, Dora Hermes, Christopher J. Honey, Robert B. Innis, Horea-Ioan Ioanas, Andrew Jahn, Agah Karakuzu, David B. Keator, Gregory Kiar, Balint Kincses, Angela R. Laird, Jonathan C. Lau, Alberto Lazari, Jon Haitz Legarreta, Adam Li, Xiangrui Li, Bradley C. Love, Hanzhang Lu, Camille Maumet, Giacomo Mazzamuto, Steven L. Meisler, Mark Mikkelsen, Henk Mutsaerts, Thomas E. Nichols, Aki Nikolaidis, Gustav Nilsonne, Guiomar Niso, Martin Norgaard, Thomas W Okell, Robert Oostenveld, Eduard Ort, Patrick J. Park, Mateusz Pawlik, Cyril R. Pernet, Franco Pestilli, Jan Petr, Christophe Phillips, Jean-Baptiste Poline, Luca Pollonini, Pradeep Reddy Raamana, Petra Ritter, Gaia Rizzo, Kay A. Robbins, Alexander P. Rockhill, Christine Rogers, Ariel Rokem, Chris Rorden, Alexandre Routier, Jose Manuel Saborit-Torres, Taylor Salo, Michael Schirner, Robert E. Smith, Tamas Spisak, Julia Sprenger, Nicole C. Swann, Martin Szinte, Sylvain Takerkart, Bertrand Thirion, Adam G. Thomas, Sajjad Torabian, Gael Varoquaux, Bradley Voytek, Julius Welzel, Martin Wilson, Tal Yarkoni, Krzysztof J. Gorgolewski

The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities.

Learning Compact Features via In-Training Representation Alignment

no code implementations23 Nov 2022 Xin Li, Xiangrui Li, Deng Pan, Yao Qiang, Dongxiao Zhu

Deep neural networks (DNNs) for supervised learning can be viewed as a pipeline of the feature extractor (i. e., last hidden layer) and a linear classifier (i. e., output layer) that are trained jointly with stochastic gradient descent (SGD) on the loss function (e. g., cross-entropy).

Representation Learning

Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints

1 code implementation14 Dec 2020 Xin Li, Xiangrui Li, Deng Pan, Dongxiao Zhu

This inspires us to propose a new Probabilistically Compact (PC) loss with logit constraints which can be used as a drop-in replacement for cross-entropy (CE) loss to improve CNN's adversarial robustness.

Adversarial Robustness

Unsupervised Self-training Algorithm Based on Deep Learning for Optical Aerial Images Change Detection

no code implementations15 Oct 2020 Yuan Zhou, Xiangrui Li

Then two set of pseudo labels are used to jointly train a student network with the same structure as the teacher.

Change Detection Earth Observation

Explainable Recommendation via Interpretable Feature Mapping and Evaluation of Explainability

no code implementations12 Jul 2020 Deng Pan, Xiangrui Li, Xin Li, Dongxiao Zhu

Latent factor collaborative filtering (CF) has been a widely used technique for recommender system by learning the semantic representations of users and items.

Collaborative Filtering Explainable Recommendation +1

On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks

1 code implementation4 Mar 2020 Xiangrui Li, Xin Li, Deng Pan, Dongxiao Zhu

Deep convolutional neural networks (CNNs) trained with logistic and softmax losses have made significant advancement in visual recognition tasks in computer vision.

Binary Classification Classification +2

Improve SGD Training via Aligning Mini-batches

no code implementations23 Feb 2020 Xiangrui Li, Deng Pan, Xin Li, Dongxiao Zhu

In each iteration of SGD, a mini-batch from the training data is sampled and the true gradient of the loss function is estimated as the noisy gradient calculated on this mini-batch.

Interpreting Age Effects of Human Fetal Brain from Spontaneous fMRI using Deep 3D Convolutional Neural Networks

no code implementations9 Jun 2019 Xiangrui Li, Jasmine Hect, Moriah Thomason, Dongxiao Zhu

The findings demonstrate that deep CNNs are a promising approach for identifying spontaneous functional patterns in fetal brain activity that discriminate age groups.

Deep Representation Learning for Road Detection through Siamese Network

no code implementations26 May 2019 Huafeng Liu, Xiaofeng Han, Xiangrui Li, Yazhou Yao, Pu Huang, Zhenming Tang

We project the LiDAR point clouds onto the image plane to generate LiDAR images and feed them into one of the branches of the network.

Autonomous Driving Representation Learning

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