← Authors

Xiaoning Qian

35 papers · 2015–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (9) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (6) πŸ—ΊοΈ Taxonomy Completionist (19) πŸƒ Academic Marathon (10) πŸ‘‘ Triple Crown 🧬 Topic Evolution πŸ† Keyword Champion (6) πŸ† Grand Slam πŸ’Ž Century Club (35) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (8) ⚑ Prolific Year (5) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (118)

Conferences

ICML (9) AISTATS (8) NIPS (7) ICLR (5) UAI (2) AAAI (1) CVPR (1) ECCV (1) MLHC (1)

Top co-authors

Byung-Jun Yoon (8) Mingyuan Zhou (8) Zhangyang Wang (7) Shuiwang Ji (6) Shuai Huang (6) Xiaofeng Qian (6) Ehsan Hajiramezanali (6) Arman Hasanzadeh (5) Guang Zhao (5) Randy Ardywibowo (5)

Keywords

uncertainty quantification (7) graph neural network (4) bayesian inference (3) bayesian learning (3) representation learning (2) activity recognition (2) feature selection (2) hamiltonian matrix (2) variational auto-encoder (2) bayesian deep learning (2) semi-implicit variational inference (2) variational inference (2) relational learning (1) link prediction (1) ensemble learning (1) domain adaptation (1) image segmentation (1) transfer learning (1) video retrieval (1) semantic segmentation (1)

Papers

Pareto Prompt Optimization ICLR 2025
GFlowNet Training by Policy Gradients ICML 2024
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution ICML 2024
Path-Guided Particle-based Sampling ICML 2024
Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting AISTATS 2024
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation NIPS 2024
Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity UAI 2024
Complete and Efficient Graph Transformers for Crystal Material Property Prediction ICLR 2024
A Space Group Symmetry Informed Network for O(3) Equivariant Crystal Tensor Prediction ICML 2024
QH9: A Quantum Hamiltonian Prediction Benchmark for QM9 Molecules NIPS 2023
Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction ICML 2023
Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian ICML 2023
Uncertainty-aware Unsupervised Video Hashing AISTATS 2023
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data MLHC 2022
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition AISTATS 2022
MoReL: Multi-omics Relational Learning ICLR 2022
VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty ICML 2022
Efficient Active Learning for Gaussian Process Classification by Error Reduction NIPS 2021
Bayesian Active Learning by Soft Mean Objective Cost of Uncertainty AISTATS 2021
Uncertainty-aware Active Learning for Optimal Bayesian Classifier ICLR 2021
Contextual Dropout: An Efficient Sample-Dependent Dropout Module ICLR 2021
Physics-constrained Automatic Feature Engineering for Predictive Modeling in Materials Science AAAI 2021
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery AISTATS 2020
NADS: Neural Architecture Distribution Search for Uncertainty Awareness ICML 2020
BayReL: Bayesian Relational Learning for Multi-omics Data Integration NIPS 2020
Bayesian Graph Neural Networks with Adaptive Connection Sampling ICML 2020
Pairwise Supervised Hashing with Bernoulli Variational Auto-Encoder and Self-Control Gradient Estimator UAI 2020
Learnable Bernoulli Dropout for Bayesian Deep Learning AISTATS 2020
Collaborative Global-Local Networks for Memory-Efficient Segmentation of Ultra-High Resolution Images CVPR 2019
Semi-Implicit Graph Variational Auto-Encoders NIPS 2019
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models AISTATS 2019
Variational Graph Recurrent Neural Networks NIPS 2019
Unsupervised CNN-based Co-Saliency Detection with Graphical Optimization ECCV 2018
Bayesian multi-domain learning for cancer subtype discovery from next-generation sequencing count data NIPS 2018
A Scalable Algorithm for Structured Kernel Feature Selection AISTATS 2015