Qian, Xiaoning

46 publications

NeurIPS 2025 A Plug-and-Play Query Synthesis Active Learning Framework for Neural PDE Solvers Zhiyuan Wang, Jinwoo Go, Byung-Jun Yoon, Nathan Urban, Xiaoning Qian

FnTML 2025 Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems Xuan Zhang, Limei Wang, Jacob Helwig, Youzhi Luo, Cong Fu, Yaochen Xie, Meng Liu, Yuchao Lin, Zhao Xu, Keqiang Yan, Keir Adams, Maurice Weiler, Xiner Li, Tianfan Fu, Yucheng Wang, Alex Strasser, Haiyang Yu, Yuqing Xie, Xiang Fu, Shenglong Xu, Yi Liu, Yuanqi Du, Alexandra Saxton, Hongyi Ling, Hannah Lawrence, Hannes Stärk, Shurui Gui, Carl Edwards, Nicholas Gao, Adriana Ladera, Tailin Wu, Elyssa F. Hofgard, Aria Mansouri Tehrani, Rui Wang, Ameya Daigavane, Montgomery Bohde, Jerry Kurtin, Qian Huang, Tuong Phung, Minkai Xu, Chaitanya K. Joshi, Simon V. Mathis, Kamyar Azizzadenesheli, Ada Fang, Alán Aspuru-Guzik, Erik J. Bekkers, Michael M. Bronstein, Marinka Zitnik, Anima Anandkumar, Stefano Ermon, Pietro Liò, Rose Yu, Stephan Günnemann, Jure Leskovec, Heng Ji, Jimeng Sun, Regina Barzilay, Tommi S. Jaakkola, Connor W. Coley, Xiaoning Qian, Xiaofeng Qian, Tess E. Smidt, Shuiwang Ji

NeurIPS 2025 C-LoRA: Contextual Low-Rank Adaptation for Uncertainty Estimation in Large Language Models Amir Hossein Rahmati, Sanket Jantre, Weifeng Zhang, Yucheng Wang, Byung-Jun Yoon, Nathan Urban, Xiaoning Qian

NeurIPS 2025 Graph-Based Symbolic Regression with Invariance and Constraint Encoding Ziyu Xiang, Kenna Ashen, Xiaofeng Qian, Xiaoning Qian

ICLR 2025 Pareto Prompt Optimization Guang Zhao, Byung-Jun Yoon, Gilchan Park, Shantenu Jha, Shinjae Yoo, Xiaoning Qian

CVPRW 2025 Scale-Invariant Implicit Neural Representations for Object Counting Siyuan Xu, Yucheng Wang, Xihaier Luo, Byung-Jun Yoon, Xiaoning Qian

ICML 2024 A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction Keqiang Yan, Alexandra Saxton, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

ICLRW 2024 Biologically Interpretable VAE with Supervision for Transcriptomics Data Under Ordinal Perturbations Seyednami Niyakan, Xihaier Luo, Byung-Jun Yoon, Xiaoning Qian

ICLR 2024 Complete and Efficient Graph Transformers for Crystal Material Property Prediction Keqiang Yan, Cong Fu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

NeurIPSW 2024 Cost-Effective Reduced-Order Modeling via Bayesian Active Learning Amir Hossein Rahmati, Nathan Urban, Byung-Jun Yoon, Xiaoning Qian

ICML 2024 GFlowNet Training by Policy Gradients Puhua Niu, Shili Wu, Mingzhou Fan, Xiaoning Qian

TMLR 2024 Hashing with Uncertainty Quantification via Sampling-Based Hypothesis Testing Yucheng Wang, Mingyuan Zhou, Xiaoning Qian

ICML 2024 Hierarchical Neural Operator Transformer with Learnable Frequency-Aware Loss Prior for Arbitrary-Scale Super-Resolution Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon

NeurIPS 2024 Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation Keqiang Yan, Xiner Li, Hongyi Ling, Kenna Ashen, Carl Edwards, Raymundo Arróyave, Marinka Zitnik, Heng Ji, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

UAI 2024 Multi-Fidelity Bayesian Optimization with Multiple Information Sources of Input-Dependent Fidelity Mingzhou Fan, Byung-Jun Yoon, Edward Dougherty, Nathan Urban, Francis Alexander, Raymundo Arróyave, Xiaoning Qian

ICML 2024 Path-Guided Particle-Based Sampling Mingzhou Fan, Ruida Zhou, Chao Tian, Xiaoning Qian

AISTATS 2024 Uncertainty-Aware Continuous Implicit Neural Representations for Remote Sensing Object Counting Siyuan Xu, Yucheng Wang, Mingzhou Fan, Byung-Jun Yoon, Xiaoning Qian

LoG 2023 A Latent Diffusion Model for Protein Structure Generation Cong Fu, Keqiang Yan, Limei Wang, Wing Yee Au, Michael Curtis McThrow, Tao Komikado, Koji Maruhashi, Kanji Uchino, Xiaoning Qian, Shuiwang Ji

ICML 2023 Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction Yuchao Lin, Keqiang Yan, Youzhi Luo, Yi Liu, Xiaoning Qian, Shuiwang Ji

ICML 2023 Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian Haiyang Yu, Zhao Xu, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

NeurIPS 2023 QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules Haiyang Yu, Meng Liu, Youzhi Luo, Alex Strasser, Xiaofeng Qian, Xiaoning Qian, Shuiwang Ji

ICMLW 2023 Reinstating Continuous Climate Patterns from Small and Discretized Data Xihaier Luo, Xiaoning Qian, Nathan Urban, Byung-Jun Yoon

AISTATS 2023 Uncertainty-Aware Unsupervised Video Hashing Yucheng Wang, Mingyuan Zhou, Yu Sun, Xiaoning Qian

AISTATS 2022 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

MLHC 2022 Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi

ICLR 2022 MoReL: Multi-Omics Relational Learning Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield, Xiaoning Qian

ICML 2022 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

AISTATS 2021 Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis J. Alexander, Xiaoning Qian

ICLR 2021 Contextual Dropout: An Efficient Sample-Dependent Dropout Module Xinjie Fan, Shujian Zhang, Korawat Tanwisuth, Xiaoning Qian, Mingyuan Zhou

NeurIPS 2021 Efficient Active Learning for Gaussian Process Classification by Error Reduction Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian

AAAI 2021 Physics-Constrained Automatic Feature Engineering for Predictive Modeling in Materials Science Ziyu Xiang, Mingzhou Fan, Guillermo Vázquez Tovar, William Trehern, Byung-Jun Yoon, Xiaofeng Qian, Raymundo Arróyave, Xiaoning Qian

ICLR 2021 Uncertainty-Aware Active Learning for Optimal Bayesian Classifier Guang Zhao, Edward Dougherty, Byung-Jun Yoon, Francis Alexander, Xiaoning Qian

NeurIPS 2020 BayReL: Bayesian Relational Learning for Multi-Omics Data Integration Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna Narayanan, Xiaoning Qian

ICML 2020 Bayesian Graph Neural Networks with Adaptive Connection Sampling Arman Hasanzadeh, Ehsan Hajiramezanali, Shahin Boluki, Mingyuan Zhou, Nick Duffield, Krishna Narayanan, Xiaoning Qian

AISTATS 2020 Learnable Bernoulli Dropout for Bayesian Deep Learning Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh, Mingyuan Zhou, Xiaoning Qian

ICML 2020 NADS: Neural Architecture Distribution Search for Uncertainty Awareness Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian

UAI 2020 Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator Siamak Zamani Dadaneh, Shahin Boluki, Mingzhang Yin, Mingyuan Zhou, Xiaoning Qian

AISTATS 2020 Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery Zepeng Huo, Arash PakBin, Xiaohan Chen, Nathan Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi

AISTATS 2019 Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian

NeurIPS 2019 Semi-Implicit Graph Variational Auto-Encoders Arman Hasanzadeh, Ehsan Hajiramezanali, Krishna Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian

NeurIPS 2019 Variational Graph Recurrent Neural Networks Ehsan Hajiramezanali, Arman Hasanzadeh, Krishna Narayanan, Nick Duffield, Mingyuan Zhou, Xiaoning Qian

NeurIPS 2018 Bayesian Multi-Domain Learning for Cancer Subtype Discovery from Next-Generation Sequencing Count Data Ehsan Hajiramezanali, Siamak Zamani Dadaneh, Alireza Karbalayghareh, Mingyuan Zhou, Xiaoning Qian

ECCV 2018 Unsupervised CNN-Based Co-Saliency Detection with Graphical Optimization Kuang-Jui Hsu, Chung-Chi Tsai, Yen-Yu Lin, Xiaoning Qian, Yung-Yu Chuang

AISTATS 2015 A Scalable Algorithm for Structured Kernel Feature Selection Shaogang Ren, Shuai Huang, John A. Onofrey, Xenios Papademetris, Xiaoning Qian

ICCV 2007 Detection of Complex Vascular Structures Using Polar Neighborhood Intensity Profile Xiaoning Qian, Matthew P. Brennan, Donald P. Dione, Lawrence W. Dobrucki

CVPRW 2006 Segmentation of Rat Cardiac Ultrasound Images with Large Dropout Regions Xiaoning Qian, Hemant D. Tagare, Zhong Tao