Ni, Yang

16 publications

JMLR 2025 Directed Cyclic Graphs for Simultaneous Discovery of Time-Lagged and Instantaneous Causality from Longitudinal Data Using Instrumental Variables Wei Jin, Yang Ni, Amanda B. Spence, Leah H. Rubin, Yanxun Xu

AISTATS 2025 Generalized Criterion for Identifiability of Additive Noise Models Using Majorization Aramayis Dallakyan, Yang Ni

ICML 2025 Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic Variables Arhit Chakrabarti, Yang Ni, Debdeep Pati, Bani Mallick

WACV 2025 Recoverable Anonymization for Pose Estimation: A Privacy-Enhancing Approach Wenjun Huang, Yang Ni, Arghavan Rezvani Dehaghani, SungHeon Evan Jeong, Hanning Chen, Yezi Liu, Fei Wen, Mohsen Imani

JMLR 2025 Sparse Semiparametric Discriminant Analysis for High-Dimensional Zero-Inflated Data Hee Cheol Chung, Yang Ni, Irina Gaynanova

WACV 2025 VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation Hanning Chen, Yang Ni, Wenjun Huang, Yezi Liu, SungHeon Jeong, Fei Wen, Nathaniel Bastian, Hugo Latapie, Mohsen Imani

JMLR 2024 Graphical Dirichlet Process for Clustering Non-Exchangeable Grouped Data Arhit Chakrabarti, Yang Ni, Ellen Ruth A. Morris, Michael L. Salinas, Robert S. Chapkin, Bani K. Mallick

ECCVW 2024 TaskCLIP: Extend Large Vision-Language Model for Task Oriented Object Detection Hanning Chen, Wenjun Huang, Yang Ni, Sanggeon Yun, Yezi Liu, Fei Wen, Alvaro Velasquez, Hugo Latapie, Mohsen Imani

IJCAI 2023 Algorithm-Hardware Co-Design for Efficient Brain-Inspired Hyperdimensional Learning on Edge (Extended Abstract) Yang Ni, Yeseong Kim, Tajana Rosing, Mohsen Imani

NeurIPS 2023 Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data Saptarshi Roy, Raymond K. W. Wong, Yang Ni

JMLR 2023 Model-Based Causal Discovery for Zero-Inflated Count Data Junsouk Choi, Yang Ni

JMLR 2022 Bayesian Covariate-Dependent Gaussian Graphical Models with Varying Structure Yang Ni, Francesco C. Stingo, Veerabhadran Baladandayuthapani

NeurIPS 2022 Bivariate Causal Discovery for Categorical Data via Classification with Optimal Label Permutation Yang Ni

UAI 2022 Causal Discovery with Heterogeneous Observational Data Fangting Zhou, Kejun He, Yang Ni

UAI 2022 Ordinal Causal Discovery Yang Ni, Bani Mallick

NeurIPS 2020 Bayesian Causal Structural Learning with Zero-Inflated Poisson Bayesian Networks Junsouk Choi, Robert Chapkin, Yang Ni