Dynamic time warping constraint learning for large margin nearest neighbor classification. - Daren Yu; Xiao Yu; Qinghua Hu; Jinfu Liu; Anqi Wu (Inf. Sci., 2011)

Weighted Task Regularization for Multitask Learning. - Yintao Liu; Anqi Wu; Dong Guo; Ke-Thia Yao; Cauligi S. Raghavendra (ICDM Workshops, 2013)

Sparse Bayesian structure learning with dependent relevance determination priors. - Anqi Wu; Mijung Park; Oluwasanmi Koyejo; Jonathan W. Pillow (NIPS, 2014)

Convolutional spike-triggered covariance analysis for neural subunit models. - Anqi Wu; Il Memming Park; Jonathan W. Pillow (NIPS, 2015)

Gaussian process based nonlinear latent structure discovery in multivariate spike train data. - Anqi Wu; Nicholas A. Roy; Stephen L. Keeley; Jonathan W. Pillow (NIPS, 2017)

Reputation in Repeated Pay-to-Bid Auctions. - Anqi Wu; Dharma Kwon; Sung Kim (AMCIS, 2018)

Learning a latent manifold of odor representations from neural responses in piriform cortex. - Anqi Wu; Stan L. Pashkovski; Sandeep R. Datta; Jonathan W. Pillow (NeurIPS, 2018)

Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks. - Anqi Wu; Sebastian Nowozin; Edward Meeds; Richard E. Turner; José Miguel Hernández-Lobato; Alexander L. Gaunt (CoRR, 2018)

Deterministic Variational Inference for Robust Bayesian Neural Networks. - Anqi Wu; Sebastian Nowozin; Edward Meeds; Richard E. Turner; José Miguel Hernández-Lobato; Alexander L. Gaunt (ICLR, 2019)

Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks. - Qi She; Anqi Wu (UAI, 2019)

Dependent relevance determination for smooth and structured sparse regression. - Anqi Wu; Oluwasanmi Koyejo; Jonathan W. Pillow (J. Mach. Learn. Res., 2019)

Bayesian latent structure discovery for large-scale neural recordings - Anqi Wu (2019)

Differentiated Prosodic Adaption of Chinese and English Poetry: An Acoustic Approach to Reading of Chinese Tang Poetry and Shakespearean Sonnets. - Yizhong Xu; Siyi Cao; Jiafang Ji; Qin Xiao; Anqi Wu; Xiuyuan Wang 003 (APSIPA, 2020)

Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking. - Anqi Wu; Estefany Kelly Buchanan; Matthew R. Whiteway; Michael Schartner; Guido Meijer; Jean-Paul Noel; Erica Rodriguez; Claire Everett; Amy Norovich; Evan Schaffer; Neeli Mishra; C. Daniel Salzman; et al. (NeurIPS, 2020)

Incorporating structured assumptions with probabilistic graphical models in fMRI data analysis. - Ming Bo Cai; Michael Shvartsman; Anqi Wu; Hejia Zhang; Xia Zhu (CoRR, 2020)

Could Government Measures Crowd Out Grassroots Philanthropy? Empirical Evidence from an Education Crowdfunding Platform. - Anqi Wu; Aravinda Garimella; Ramanath Subramanyam (HICSS, 2021)

Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity. - Felix Pei; Joel Ye; David M. Zoltowski; Anqi Wu; Raeed H. Chowdhury; Hansem Sohn; Joseph E. O'Doherty; Krishna V. Shenoy; Matthew T. Kaufman; Mark M. Churchland; Mehrdad Jazayeri; Lee E. Miller; et al. (NeurIPS Datasets and Benchmarks, 2021)

Domain Generalization via Domain-based Covariance Minimization. - Anqi Wu (CoRR, 2021)

Accessibility Assessment of Buildings Based on Multi-Source Spatial Data: Taking Wuhan as a Case Study. - Xue Yang 002; Yanjia Cao; Anqi Wu; Mingqiang Guo; Zhen Dong 005; Luliang Tang (ISPRS Int. J. Geo Inf., 2021)

Brain kernel: A new spatial covariance function for fMRI data. - Anqi Wu; Samuel A. Nastase; Christopher Baldassano; Nicholas B. Turk-Browne; Kenneth A. Norman; Barbara E. Engelhardt; Jonathan W. Pillow (NeuroImage, 2021)

Partitioning variability in animal behavioral videos using semi-supervised variational autoencoders. - Matthew R. Whiteway; Dan Biderman; Yoni Friedman; Mario Dipoppa; Estefany Kelly Buchanan; Anqi Wu; John Zhou; Niccolò Bonacchi; Nathaniel J. Miska; Jean-Paul Noel; Erica Rodriguez; Michael Schartner; et al. (PLoS Comput. Biol., 2021)

Disaster Management Through Digital Platforms: Online Crowdfunding Communities Respond to the COVID-19 Pandemic. - Anqi Wu; Aravinda Garimella; Ramanath Subramanyam; Eren Ahsen (HICSS, 2022)

HFL-Net: Highlight Foreground and Local Scale Features Network for Cross-Domain Ship Detection. - Anqi Wu; Qiqi Zhu (IGARSS, 2022)

SemiMultiPose: A Semi-supervised Multi-animal Pose Estimation Framework. - Ari Blau; Christoph Gebhardt; Andrés Bendesky; Liam Paninski; Anqi Wu (CoRR, 2022)

Improving Accessibility of Educational Content - An Exploratory Data Analysis. - Anqi Wu; Arijit Sengupta (ICIS, 2023)

Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Model. - Yule Wang; Zijing Wu; Chengrui Li; Anqi Wu (NeurIPS, 2023)

Inverse Reinforcement Learning with the Average Reward Criterion. - Feiyang Wu; Jingyang Ke; Anqi Wu (NeurIPS, 2023)

JGAT: a joint spatio-temporal graph attention model for brain decoding. - Han Yi Chiu; Liang Zhao; Anqi Wu (CoRR, 2023)

Forward χ2 Divergence Based Variational Importance Sampling. - Chengrui Li; Yule Wang; Weihan Li; Anqi Wu (CoRR, 2023)

One-hot Generalized Linear Model for Switching Brain State Discovery. - Chengrui Li; Soon Ho Kim; Chris Rodgers; Hannah Choi; Anqi Wu (ICLR, 2024)

Forward χ2 Divergence Based Variational Importance Sampling. - Chengrui Li; Yule Wang; Weihan Li; Anqi Wu (ICLR, 2024)

Multi-Region Markovian Gaussian Process: An Efficient Method to Discover Directional Communications Across Multiple Brain Regions. - Weihan Li; Chengrui Li; Yule Wang; Anqi Wu (ICML, 2024)

A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing. - Chengrui Li; Weihan Li; Yule Wang; Anqi Wu (ICML, 2024)

Infer and Adapt: Bipedal Locomotion Reward Learning from Demonstrations via Inverse Reinforcement Learning. - Feiyang Wu; Zhaoyuan Gu; Hanran Wu; Anqi Wu; Ye Zhao 002 (ICRA, 2024)

Enhancing Evapotranspiration Estimations Using a Single Source Energy Balance Model with Input of Composited Thermal Infrared Temperatures. - Anqi Wu; Yazhen Jiang; Ronglin Tang; Zhao-Liang Li (IGARSS, 2024)

Exploring Behavior-Relevant and Disentangled Neural Dynamics with Generative Diffusion Models. - Yule Wang; Chengrui Li; Weihan Li; Anqi Wu (NeurIPS, 2024)

Learn to Teach: Improve Sample Efficiency in Teacher-student Learning for Sim-to-Real Transfer. - Feiyang Wu; Zhaoyuan Gu; Ye Zhao 002; Anqi Wu (CoRR, 2024)

NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human. - Shuo Huang; William MacLean; Xiaoxi Kang; Anqi Wu; Lizhen Qu; Qiongkai Xu; Zhuang Li 001; Xingliang Yuan; Gholamreza Haffari (CoRR, 2024)

Markovian Gaussian Process: A Universal State-Space Representation for Stationary Temporal Gaussian Process. - Weihan Li; Yule Wang; Chengrui Li; Anqi Wu (CoRR, 2024)

Inverse Kernel Decomposition. - Chengrui Li; Anqi Wu (Trans. Mach. Learn. Res., 2024)

Cluster Assumption-Guided Timestamp-Supervised Temporal Action Segmentation. - Ziyou Ren; Guozhang Li; Nan Cheng; Anqi Wu; Nannan Wang 001; Xinbo Gao 001 (IEEE Trans. Multim., 2025)

Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors. - Jingyang Ke; Feiyang Wu; Jiyi Wang; Jeffrey Markowitz; Anqi Wu (CoRR, 2025)

A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement. - Chengrui Li; Yunmiao Wang; Yule Wang; Weihan Li; Dieter Jaeger; Anqi Wu (CoRR, 2025)

EmoBipedNav: Emotion-aware Social Navigation for Bipedal Robots with Deep Reinforcement Learning. - Wei Zhu 028; Abirath Raju; Abdulaziz Shamsah; Anqi Wu; Seth A. Hutchinson; Ye Zhao 002 (CoRR, 2025)

Learning Task-Agnostic Skill Bases to Uncover Motor Primitives in Animal Behaviors. - Jiyi Wang; Jingyang Ke; Bo Dai 001; Anqi Wu (CoRR, 2025)

Learn to Teach: Sample-Efficient Privileged Learning for Humanoid Locomotion Over Real-World Uneven Terrain. - Feiyang Wu; Xavier Nal; Jaehwi Jang; Wei Zhu 028; Zhaoyuan Gu; Anqi Wu; Ye Zhao 002 (IEEE Robotics Autom. Lett., 2025)