Wu, Ga

11 publications

ICLR 2025 Data-Centric Prediction Explanation via Kernelized Stein Discrepancy Mahtab Sarvmaili, Hassan Sajjad, Ga Wu

ICML 2025 Resolving Lexical Bias in Model Editing Hammad Rizwan, Domenic Rosati, Ga Wu, Hassan Sajjad

ICLR 2024 Self-Supervised Representation Learning from Random Data Projectors Yi Sui, Tongzi Wu, Jesse C. Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs

NeurIPSW 2023 Self-Supervised Representation Learning from Random Data Projectors Yi Sui, Tongzi Wu, Jesse Cresswell, Ga Wu, George Stein, Xiao Shi Huang, Xiaochen Zhang, Maksims Volkovs

MLJ 2022 Arbitrary Conditional Inference in Variational Autoencoders via Fast Prior Network Training Ga Wu, Justin Domke, Scott Sanner

AAAI 2022 PUMA: Performance Unchanged Model Augmentation for Training Data Removal Ga Wu, Masoud Hashemi, Christopher Srinivasa

NeurIPS 2021 Representer Point Selection via Local Jacobian Expansion for Post-Hoc Classifier Explanation of Deep Neural Networks and Ensemble Models Yi Sui, Ga Wu, Scott Sanner

JAIR 2020 Scalable Planning with Deep Neural Network Learned Transition Models Ga Wu, Buser Say, Scott Sanner

IJCAI 2017 Nonlinear Hybrid Planning with Deep Net Learned Transition Models and Mixed-Integer Linear Programming Buser Say, Ga Wu, Yu Qing Zhou, Scott Sanner

NeurIPS 2017 Scalable Planning with TensorFlow for Hybrid Nonlinear Domains Ga Wu, Buser Say, Scott Sanner

AAAI 2015 Bayesian Model Averaging Naive Bayes (BMA-NB): Averaging over an Exponential Number of Feature Models in Linear Time Ga Wu, Scott Sanner, Rodrigo F. S. C. Oliveira