Xiaoning Qian

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