| 2025 | CVPR | Scale-Invariant Implicit Neural Representations For Object Counting. | Siyuan Xu, Yucheng Wang, Xihaier Luo, Byung-Jun Yoon, Xiaoning Qian |
| 2025 | ICLR | Pareto Prompt Optimization. | Guang Zhao, Byung-Jun Yoon, Gilchan Park, Shantenu Jha, Shinjae Yoo, Xiaoning Qian |
| 2024 | AISTATS | Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting. | Siyuan Xu, Yucheng Wang, Mingzhou Fan, Byung-Jun Yoon, Xiaoning Qian |
| 2024 | ICASSP | Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks. | Sanket R. Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon |
| 2024 | ICLR | Complete and Efficient Graph Transformers for Crystal Material Property Prediction. | Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji |
| 2024 | ICML | Path-Guided Particle-based Sampling. | Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian |
| 2024 | ICML | Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution. | Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon |
| 2024 | ICML | GFlowNet Training by Policy Gradients. | Puhua Niu, Shili Wu, Mingzhou Fan, Xiaoning Qian |
| 2024 | ICML | A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction. | Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji |
| 2024 | ICPR | When Uncertainty-Based Active Learning May Fail? | Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian |
| 2024 | KDD | Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data. | Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield |
| 2024 | WWW | Towards Invariant Time Series Forecasting in Smart Cities. | Ziyi Zhang, Shaogang Ren, Xiaoning Qian, Nick Duffield |
| 2024 | UAI | Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity. | Mingzhou Fan, Byung-Jun Yoon, Edward R. Dougherty, Nathan M. Urban, Francis J. Alexander, Raymundo Arryave, Xiaoning Qian |
| 2023 | AISTATS | Uncertainty-aware Unsupervised Video Hashing. | Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian |
| 2023 | ICML | Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction. | Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji |
| 2023 | ICML | Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian. | Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji |
| 2022 | AISTATS | VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition. | Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian |
| 2022 | ICASSP | Adaptive Group Testing with Mismatched Models. | Mingzhou Fan, Byung-Jun Yoon, Francis J. Alexander, Edward R. Dougherty, Xiaoning Qian |
| 2022 | ICASSP | Dynimp: Dynamic Imputation for Wearable Sensing Data through Sensory and Temporal Relatedness. | Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi |
| 2022 | ICLR | MoReL: Multi-omics Relational Learning. | Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian |
| 2022 | ICML | VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty. | Randy Ardywibowo, Zepeng Huo, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian |
| 2022 | SENSYS | Attention-Based Deep Bayesian Counting For AI-Augmented Agriculture. | Yucheng Wang, Mengmeng Gu, Mingyuan Zhou, Xiaoning Qian |
| 2021 | AAAI | Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science. | Ziyu Xiang, Mingzhou Fan, Guillermo Vzquez Tovar, William Trehern, Byung-Jun Yoon, Xiaofeng Qian, Raymundo Arryave, Xiaoning Qian |
| 2021 | AISTATS | Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty. | Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian |
| 2021 | ICLR | Contextual Dropout: An Efficient Sample-Dependent Dropout Module. | Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou |
| 2021 | ICLR | Uncertainty-aware Active Learning for Optimal Bayesian Classifier. | Guang Zhao, Edward R. Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian |
| 2020 | AISTATS | Learnable Bernoulli Dropout for Bayesian Deep Learning. | Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian |
| 2020 | AISTATS | Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. | Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi |
| 2020 | BMVC | Neural Network Quantization with Scale-Adjusted Training. | Qing Jin, Linjie Yang, Zhenyu Liao, Xiaoning Qian |
| 2020 | ICASSP | Arsm Gradient Estimator for Supervised Learning to Rank. | Siamak Zamani Dadaneh, Shahin Boluki, Mingyuan Zhou, Xiaoning Qian |
| 2020 | ICASSP | Semi-Implicit Stochastic Recurrent Neural Networks. | Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian |
| 2020 | ICML | NADS: Neural Architecture Distribution Search for Uncertainty Awareness. | Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian |
| 2020 | ICML | Bayesian Graph Neural Networks with Adaptive Connection Sampling. | Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian |
| 2020 | ICPR | GPSRL: Learning Semi-Parametric Bayesian Survival Rule Lists from Heterogeneous Patient Data. | Ameer Hamza Shakur, Xiaoning Qian, Zhangyang Wang, Bobak Mortazavi, Shuai Huang |
| 2020 | UAI | Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator. | Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian |
| 2019 | AISTATS | Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models. | Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian |
| 2019 | CVPR | Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images. | Wuyang Chen, Ziyu Jiang, Zhangyang Wang, Kexin Cui, Xiaoning Qian |
| 2019 | MICCAI | Cone-Beam Computed Tomography (CBCT) Segmentation by Adversarial Learning Domain Adaptation. | Xiaoqian Jia, Sicheng Wang, Xiao Liang, Anjali Balagopal, Dan Nguyen, Ming Yang, Zhangyang Wang, Jim Xiuquan Ji, Xiaoning Qian, Steve B. Jiang |
| 2018 | ACSSC | Robust Smoothing for State-Space Models with Unknown Noise Statistics. | Roozbeh Dehghannasiri, Xiaoning Qian, Edward R. Dougherty |
| 2018 | ECCV | Unsupervised CNN-Based Co-saliency Detection with Graphical Optimization. | Kuang-Jui Hsu, Chung-Chi Tsai, Yen-Yu Lin, Xiaoning Qian, Yung-Yu Chuang |
| 2018 | ICTAI | Recursive Structure Similarity: A Novel Algorithm for Graph Clustering. | Yixin Fang, Ruoming Jin, Wei Xiong, Xiaoning Qian, Dejing Dou, Hai Phan |
| 2017 | ACSSC | Bayesian Kalman filtering in the presence of unknown noise statistics using factor graphs. | Roozbeh Dehghannasiri, Mohammad Shahrokh Esfahani, Xiaoning Qian, Edward R. Dougherty |
| 2017 | ACSSC | An objective-based experimental design framework for signal processing in the context of canonical expansions. | Roozbeh Dehghannasiri, Xiaoning Qian, Edward R. Dougherty |
| 2017 | ICASSP | Image co-saliency detection via locally adaptive saliency map fusion. | Chung-Chi Tsai, Xiaoning Qian, Yen-Yu Lin |
| 2017 | ICIP | Noise-tolerant deep learning for histopathological image segmentation. | Weizhi Li, Xiaoning Qian, Jim Jing-Yan Ji |
| 2016 | ICASSP | Co-segmentation of multiple images through random walk on graphs. | Yijie Wang, Byung-Jun Yoon, Xiaoning Qian |
| 2015 | AISTATS | A Scalable Algorithm for Structured Kernel Feature Selection. | Shaogang Ren, Shuai Huang, John A. Onofrey, Xenios Papademetris, Xiaoning Qian |
| 2015 | SDM | Domain-Knowledge Driven Cognitive Degradation Modeling for Alzheimer's Disease. | Ying Lin, Kaibo Liu, Eunshin Byon, Xiaoning Qian, Shuai Huang |
| 2014 | ICASSP | Structured sparse PCA to identify miRNA co-regulatory modules. | Shaogang Ren, Xiaoning Qian |
| 2014 | ICASSP | Joint clustering of protein interaction networks by block modeling. | Yijie Wang, Xiaoning Qian |
| 2013 | IROS | Functional analysis of grasping motion. | Wei Dai, Yu Sun, Xiaoning Qian |
| 2013 | MICCAI | Simultaneous Tracking, 3D Reconstruction and Deforming Point Detection for Stereoscope Guided Surgery. | Bingxiong Lin, Adrian S. Johnson, Xiaoning Qian, Jaime Snchez, Yu Sun |
| 2012 | ICASSP | Structural intervention of gene regulatory networks by general rank-k matrix perturbation. | Xiaoning Qian, Byung-Jun Yoon, Edward R. Dougherty |
| 2011 | ACSSC | Session TA8a1: Signal processing methods for representation, analysis, and control of biological systems. | Byung-Jun Yoon, Xiaoning Qian |
| 2011 | ICASSP | Contour-based hidden Markov model to segment 2D ultrasound images. | Xiaoning Qian, Byung-Jun Yoon |
| 2010 | ICASSP | Shape matching based on graph alignment using hidden Markov models. | Xiaoning Qian, Byung-Jun Yoon |
| 2007 | ICCV | Detection of Complex Vascular Structures using Polar Neighborhood Intensity Profile. | Xiaoning Qian, Matthew P. Brennan, Donald P. Dione, Lawrence W. Dobrucki |
| 2006 | CVPR | Segmentation of Rat Cardiac Ultrasound Images with Large Dropout Regions. | Xiaoning Qian, Hemant D. Tagare, Zhong Tao |
| 2005 | MICCAI | Optimal Embedding for Shape Indexing in Medical Image Databases. | Xiaoning Qian, Hemant D. Tagare |