Wu, Anqi

19 publications

ICML 2025 Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors Jingyang Ke, Feiyang Wu, Jiyi Wang, Jeffrey Markowitz, Anqi Wu

ICML 2025 Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes Weihan Li, Yule Wang, Chengrui Li, Anqi Wu

IJCAI 2025 Towards Fairness with Limited Demographics via Disentangled Learning Zichong Wang, Anqi Wu, Nuno Moniz, Shu Hu, Bart P. Knijnenburg, Xingquan Zhu, Wenbin Zhang

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

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

ICLR 2024 Forward $\chi^2$ Divergence Based Variational Importance Sampling Chengrui Li, Yule Wang, Weihan Li, Anqi Wu

TMLR 2024 Inverse Kernel Decomposition Chengrui Li, Anqi Wu

ICML 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

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

NeurIPS 2023 Extraction and Recovery of Spatio-Temporal Structure in Latent Dynamics Alignment with Diffusion Models 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 2020 Deep Graph Pose: A Semi-Supervised Deep Graphical Model for Improved Animal Pose Tracking Anqi Wu, Estefany 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 The International Brain Laboratory, John P. Cunningham, Liam Paninski

JMLR 2019 Dependent Relevance Determination for Smooth and Structured Sparse Regression Anqi Wu, Oluwasanmi Koyejo, Jonathan Pillow

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

UAI 2019 Neural Dynamics Discovery via Gaussian Process Recurrent Neural Networks Qi She, Anqi Wu

NeurIPS 2018 Learning a Latent Manifold of Odor Representations from Neural Responses in Piriform Cortex Anqi Wu, Stan Pashkovski, Sandeep R Datta, Jonathan W Pillow

NeurIPS 2017 Gaussian Process Based Nonlinear Latent Structure Discovery in Multivariate Spike Train Data Anqi Wu, Nicholas A. Roy, Stephen Keeley, Jonathan W Pillow

NeurIPS 2015 Convolutional Spike-Triggered Covariance Analysis for Neural Subunit Models Anqi Wu, ll Memming Park, Jonathan W Pillow

NeurIPS 2014 Sparse Bayesian Structure Learning with “dependent Relevance Determination” Priors Anqi Wu, Mijung Park, Oluwasanmi O Koyejo, Jonathan W Pillow