Publications

New publication update please refer to here.

Thesis

Bayesian latent structure discovery for large-scale neural recordings, [thesis][ProQuest]

Anqi Wu

Preprints

SemiMultiPose: A Semi-supervised Multi-animal Pose Estimation Framework, arXiv 2204.07072, [arXiv]

Ari Blau, Christoph Gebhardt, Andres Bendesky, Liam Paninski, Anqi Wu

Domain Generalization via Domain-based Covariance Minimization, arXiv 2110.06298, [arXiv]

Anqi Wu

Exploiting gradients and Hessians in Bayesian optimization and Bayesian quadrature, arXiv 1704.00060, [arXiv]

Anqi Wu, Mikio C. Aoi, and Jonathan W. Pillow

Journal Articles

Partitioning variability in behavioral videos using semi-supervised deep generative models, PLOS Computational Biology. [PLOS][bioRxiv][code]

Matthew R. Whiteway, Dan Biderman, Yoni Friedman, Mario Dipoppa, E. Kelly Buchanan, Anqi Wu, John Zhou, Niccolò Bonacchi, Nathaniel J. Miska, Jean-Paul Noel, Erica Rodriguez, Michael Schartner, Karolina Socha, Anne E. Urai, C. Daniel Salzman, The International Brain Laboratory, John P. Cunningham, Liam Paninski.

Brain kernel: a new spatial covariance function for fMRI data, NeuroImage. [web link][bioRxiv][code]

Anqi Wu, Samuel A. Nastase, Christopher A. Baldassano, Nicholas B. Turk-Browne, Kenneth A. Norman, Barbara E. Engelhardt, Jonathan W. Pillow.

Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis , Neuropsychologia, [arXiv][web link]

Mingbo Cai, Michael Shvartsman, Anqi Wu, Hejia Zhang, and Xia Zhu (all authors contributed equally)

Dependent relevance determination for smooth and structured sparse regression, Journal of Machine Learning Research (JMLR), [JMLR][arXiv][code]

Anqi Wu, Oluwasanmi Koyejo, and Jonathan W. Pillow

Dynamic time warping constraint learning for large margin nearest neighbor classification, Information Sciences. 181.13 (2011), [paper][web link]

Daren Yu, Xiao Yu, Qinghua Hu, Jinfu Liu, and Anqi Wu

Peer Reviewed Conference Proceedings

Neural Latents Benchmark ‘21: Evaluating latent variable models of neural population activity, NeurIPS 2021 Datasets and Benchmarks Track. [arXiv][github.io]

Felix Pei, Joel Ye, David Zoltowski, Anqi Wu, Raeed H. Chowdhury, Hansem Sohn, Joseph E. O’Doherty, Krishna V. Shenoy, Matthew T. Kaufman, Mark Churchland, Mehrdad Jazayeri, Lee E. Miller, Jonathan Pillow, Il Memming Park, Eva L. Dyer, Chethan Pandarinath.

Semi-supervised sequence modeling for improved behavioral segmentation, CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling, in conjunction with Computer Vision and Pattern Recognition (CVPR), 2021. [bioRxiv][code]

Matthew R Whiteway, Evan S Schaffer, Anqi Wu, E Kelly Buchanan, Omer F Onder, Neeli Mishra, Liam Paninski.

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking, Advances in Neural Information Processing Systems (NeurIPS), 2020, (acceptance rate: 20%), [paper][bioRxiv][code][neurocaas]

Anqi Wu*, E. Kelly Buchanan*, Matthew Whiteway, Michael Schartner, Guido Meijer, Jean-Paul Noel, Erica Rodriguez, Claire Everett, Amy Norovich, Evan Schaffer, Neeli Mishra, C. Daniel Salzman, Dora Angelaki, Andrés Bendesky, The International Brain Laboratory, John Cunningham, and Liam Paninski

(* equal contribution)

Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks , Conference on Uncertainty in Artificial Intelligence (UAI), 2019, (oral presentation: 6.8%), [paper][code][talk]

Roger She, Anqi Wu

Deterministic variational inference for robust Bayesian neural networks, Seventh International Conference on Learning Representations (ICLR), 2019, (oral presentation: 1.5%), [paper][code-tensorflow][code-tensor2tensor][talk]

Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, and Alexander L. Gaunt

Learning a latent manifold of odor representations from neural responses in piriform cortex, Advances in Neural Information Processing Systems (NIPS), 2018, (acceptance rate: 20.67%), [paper][code]

Anqi Wu, Stan Pashkovski, Bob Datta, and Jonathan W Pillow

Gaussian process based nonlinear latent structure discovery in multivariate spike train data, Advances in Neural Information Processing Systems (NIPS), 2017, (acceptance rate: 20.93%), [paper][code]

Anqi Wu, Nicholas Roy, Stephen Keeley, and Jonathan W Pillow

Convolutional spike-triggered covariance analysis for neural subunit models, Advances in Neural Information Processing Systems (NIPS), 2015, (acceptance rate: 21.93%), [paper][code]

Anqi Wu, Il Memming Park, and Jonathan W. Pillow

Sparse bayesian structure learning with dependent relevance determination priors, Advances in Neural Information Processing Systems (NIPS), 2014, (acceptance rate: 24.67%), [paper][code]

Anqi Wu, Mijung Park, Oluwasanmi O. Koyejo, and Jonathan W. Pillow

Weighted task regularization for multitask learning, IEEE 13th International Conference on Data Mining Workshops (ICDMW), 2013, [paper][web link]

Yintao Liu, Anqi Wu, Dong Guo, Ke-Thia Yao, and Cauligi S. Raghavendra

Global model for failure prediction for rod pump artificial lift systems, SPE Western Regional & AAPG Pacific Section Meeting 2013 Joint Technical Conference, [paper][web link]

Cauligi S. Raghavendra, Yintao Liu, Anqi Wu, Oluwafemi Balogun, Iraj Ershaghi, Jingwen Zheng, Dong Guo, and Ke-Thia Yao

Making the nearest neighbor meaningful for time series classification, The 4th International Congress on Image and Signal Processing, 2011, [paper][web link]

Daren Yu, Xiao Yu, and Anqi Wu

Large margin dimensionality reduction for time series, The first International Conference on Pervasive Computation, Signal Processing and Applications, 2010, [paper][web link]

Xiao Yu, Anqi Wu, and Daren Yu

Abstracts

Semi-supervised sequence modeling for improved behavior segmentation, Computational and Systems Neuroscience (Cosyne), 2022

Matt Whiteway, Anqi Wu, Mia Bramel, Kelly Buchanan, Catherine Chen, Neeli Mishra, Evan Schaffer, Andres Villegas, The International Brain Laboratory, and Liam Paninski

SemiMultiPose: A Semi-supervised Multi-animal Pose Estimation Framework, Computational and Systems Neuroscience (Cosyne), 2022

Ari Blau, Christoph Gebhardt, Andrés Bendesky, Liam Paninski, and Anqi Wu

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking, Computational and Systems Neuroscience (Cosyne), 2021

Gradient-based analysis of wide-field calcium imagining data using Gaussian processes, Computational and Systems Neuroscience (Cosyne), 2019

Mikio Aoi, Benjamin Scott, Anqi Wu, Stephan Thiberge, Carlos Brody, David W. Tank, and Jonathan Pillow

Learning a latent manifold of odor representations in piriform cortex, Computational and Systems Neuroscience (Cosyne), 2019, (oral presentation: 3%), [talk]

Anqi Wu, Stan Pashkovski, Bob Datta, and Jonathan W Pillow

Extracting nonlinear manifolds from spike train data with Gaussian process latent variables, Computational and Systems Neuroscience (Cosyne), 2018

Anqi Wu, Nicholas Roy, Stephen Keeley, and Jonathan W. Pillow

Brain Kernel: A covariance function for fMRI data using a large-scale Gaussian process latent variable model, The 11th conference on Bayesian Nonparametrics (BNP), 2017 (oral presentation)

Anqi Wu, Barbara Engelhardt, and Jonathan W. Pillow

A Bayesian approach to structured sparsity for fMRI decoding, Computational and Systems Neuroscience (Cosyne), 2016

Anqi Wu, Oluwasanmi Koyejo, and Jonathan W. Pillow

Convolutional spike-triggered covariance analysis for characterizing subunit models, Computational and Systems Neuroscience (Cosyne), 2015

Anqi Wu, Il Memming Park, and Jonathan W. Pillow

Patent

Global model for failure prediction for artificial lift systems, US Patent 9,292,799, 2016, [web link]

Yintao Liu, Ke-Thia Yao, Cauligi S. Raghavendra, Anqi Wu, Dong Guo, Jingwen Zheng, Lanre Olabinjo, Oluwafemi Balogun, and Iraj Ershaghi