Xiaoning Qian
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View article: InvarGC: Invariant Granger Causality for Heterogeneous Interventional Time Series under Latent Confounding
InvarGC: Invariant Granger Causality for Heterogeneous Interventional Time Series under Latent Confounding Open
Granger causality is widely used for causal structure discovery in complex systems from multivariate time series data. Traditional Granger causality tests based on linear models often fail to detect even mild non-linear causal relationship…
View article: Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification
Data-Augmented Few-Shot Neural Emulator for Computer-Model System Identification Open
Partial differential equations (PDEs) underpin the modeling of many natural and engineered systems. It can be convenient to express such models as neural PDEs rather than using traditional numerical PDE solvers by replacing part or all of …
View article: CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death
CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death Open
Coxiella burnetii (Cb), the causative agent of Q fever, replicates within host macrophages by modulating immune responses through poorly understood mechanisms. Long non-coding RNAs (lncRNAs) are crucial yet underexplored regulators of infl…
View article: A Benchmark for Quantum Chemistry Relaxations via Machine Learning Interatomic Potentials.
A Benchmark for Quantum Chemistry Relaxations via Machine Learning Interatomic Potentials. Open
Computational quantum chemistry plays a critical role in drug discovery, chemical synthesis, and materials science. While first-principles methods, such as density functional theory (DFT), provide high accuracy in modeling electronic struc…
View article: Cost-effective Reduced-Order Modeling via Bayesian Active Learning
Cost-effective Reduced-Order Modeling via Bayesian Active Learning Open
Machine Learning surrogates have been developed to accelerate solving systems dynamics of complex processes in different science and engineering applications. To faithfully capture governing systems dynamics, these methods rely on large tr…
View article: PhenoGraph: A Multi-Agent Framework for Phenotype-driven Discovery in Spatial Transcriptomics Data Augmented with Knowledge Graphs
PhenoGraph: A Multi-Agent Framework for Phenotype-driven Discovery in Spatial Transcriptomics Data Augmented with Knowledge Graphs Open
Spatial transcriptomics (ST) provides powerful insights into gene expression patterns within tissue structures, enabling the discovery of molecular mechanisms in complex tumor microenvironments (TMEs). Phenotype-based discovery in ST data …
View article: Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting
Uncertainty-aware Continuous Implicit Neural Representations for Remote Sensing Object Counting Open
Many existing object counting methods rely on density map estimation (DME) of the discrete grid representation by decoding extracted image semantic features from designed convolutional neural networks (CNNs). Relying on discrete density ma…
View article: Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation
Invariant Tokenization of Crystalline Materials for Language Model Enabled Generation Open
We consider the problem of crystal materials generation using language models (LMs). A key step is to convert 3D crystal structures into 1D sequences to be processed by LMs. Prior studies used the crystallographic information framework (CI…
View article: Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis
Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis Open
Identification of protein-protein interactions (PPIs) helps derive cellular mechanistic understanding, particularly in the context of complex conditions such as neurodegenerative disorders, metabolic syndromes, and cancer. Large Language M…
View article: CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death.
CYP1B1-AS1 regulates CYP1B1 to promote Coxiella burnetii pathogenesis by inhibiting ROS and host cell death. Open
View article: Epidemiological Model Calibration via Graybox Bayesian Optimization
Epidemiological Model Calibration via Graybox Bayesian Optimization Open
In this study, we focus on developing efficient calibration methods via Bayesian decision-making for the family of compartmental epidemiological models. The existing calibration methods usually assume that the compartmental model is cheap …
View article: Path-Guided Particle-based Sampling
Path-Guided Particle-based Sampling Open
Particle-based Bayesian inference methods by sampling from a partition-free target (posterior) distribution, e.g., Stein variational gradient descent (SVGD), have attracted significant attention. We propose a path-guided particle-based sam…
View article: Hyperparameter Tuning Through Pessimistic Bilevel Optimization
Hyperparameter Tuning Through Pessimistic Bilevel Optimization Open
Automated hyperparameter search in machine learning, especially for deep learning models, is typically formulated as a bilevel optimization problem, with hyperparameter values determined by the upper level and the model learning achieved b…
View article: LoRA-BERT: a Natural Language Processing Model for Robust and Accurate Prediction of long non-coding RNAs
LoRA-BERT: a Natural Language Processing Model for Robust and Accurate Prediction of long non-coding RNAs Open
Long non-coding RNAs (lncRNAs) serve as crucial regulators in numerous biological processes. Although they share sequence similarities with messenger RNAs (mRNAs), lncRNAs perform entirely different roles, providing new avenues for biologi…
View article: Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data Open
The world is moving towards clean and renewable energy sources, such as wind energy, in an attempt to reduce greenhouse gas emissions that contribute to global warming. To enhance the analysis and storage of wind data, we introduce a deep …
View article: Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data
Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data Open
View article: Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data
Learning Flexible Time-windowed Granger Causality Integrating Heterogeneous Interventional Time Series Data Open
Granger causality, commonly used for inferring causal structures from time\nseries data, has been adopted in widespread applications across various fields\ndue to its intuitive explainability and high compatibility with emerging deep\nneur…
View article: Understanding Uncertainty-based Active Learning Under Model Mismatch
Understanding Uncertainty-based Active Learning Under Model Mismatch Open
Instead of randomly acquiring training data points, Uncertainty-based Active Learning (UAL) operates by querying the label(s) of pivotal samples from an unlabeled pool selected based on the prediction uncertainty, thereby aiming at minimiz…
View article: GFlowNet Training by Policy Gradients
GFlowNet Training by Policy Gradients Open
Generative Flow Networks (GFlowNets) have been shown effective to generate combinatorial objects with desired properties. We here propose a new GFlowNet training framework, with policy-dependent rewards, that bridges keeping flow balance o…
View article: Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys
Data-driven study of composition-dependent phase compatibility in NiTi shape memory alloys Open
The martensitic transformation in NiTi-based Shape Memory Alloys (SMAs)\nprovides a basis for shape memory effect and superelasticity, thereby enabling\napplications requiring solid-state actuation and large recoverable shape\nchanges upon…
View article: Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution Open
In this work, we present an arbitrary-scale super-resolution (SR) method to enhance the resolution of scientific data, which often involves complex challenges such as continuity, multi-scale physics, and the intricacies of high-frequency s…
View article: Pathway-based analyses of gene expression profiles at low doses of ionizing radiation
Pathway-based analyses of gene expression profiles at low doses of ionizing radiation Open
Radiation exposure poses a significant threat to human health. Emerging research indicates that even low-dose radiation once believed to be safe, may have harmful effects. This perception has spurred a growing interest in investigating the…
View article: Towards Invariant Time Series Forecasting in Smart Cities
Towards Invariant Time Series Forecasting in Smart Cities Open
In the transformative landscape of smart cities, the integration of the cutting-edge web technologies into time series forecasting presents a pivotal opportunity to enhance urban planning, sustainability, and economic growth. The advanceme…
View article: Towards Invariant Time Series Forecasting in Smart Cities
Towards Invariant Time Series Forecasting in Smart Cities Open
In the transformative landscape of smart cities, the integration of the cutting-edge web technologies into time series forecasting presents a pivotal opportunity to enhance urban planning, sustainability, and economic growth. The advanceme…
View article: MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance
MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance Open
View article: Biologically Interpretable VAE with Supervision for Transcriptomics Data Under Ordinal Perturbations
Biologically Interpretable VAE with Supervision for Transcriptomics Data Under Ordinal Perturbations Open
A bstract Latent variable models such as the Variational Auto-Encoders (VAEs) have shown impressive performance for inferring expression patterns for cell subtyping and biomarker identification from transcriptomics data. However, the limit…
View article: Complete and Efficient Graph Transformers for Crystal Material Property Prediction
Complete and Efficient Graph Transformers for Crystal Material Property Prediction Open
Crystal structures are characterized by atomic bases within a primitive unit cell that repeats along a regular lattice throughout 3D space. The periodic and infinite nature of crystals poses unique challenges for geometric graph representa…
View article: Dynamic Incremental Optimization for Best Subset Selection
Dynamic Incremental Optimization for Best Subset Selection Open
Best subset selection is considered the `gold standard' for many sparse learning problems. A variety of optimization techniques have been proposed to attack this non-smooth non-convex problem. In this paper, we investigate the dual forms o…
View article: Causal Bayesian Optimization via Exogenous Distribution Learning
Causal Bayesian Optimization via Exogenous Distribution Learning Open
Maximizing a target variable as an operational objective in a structural causal model is an important problem. Causal Bayesian Optimization~(CBO) methods either rely on interventions that alter the causal structure to maximize the reward; …
View article: Multi-modal Representation Learning for Cross-modal Prediction of Continuous Weather Patterns from Discrete Low-Dimensional Data
Multi-modal Representation Learning for Cross-modal Prediction of Continuous Weather Patterns from Discrete Low-Dimensional Data Open
World is looking for clean and renewable energy sources that do not pollute the environment, in an attempt to reduce greenhouse gas emissions that contribute to global warming. Wind energy has significant potential to not only reduce green…