papers

Publications (17)

q-bio.MN2025

Input-to-state stability-based chemical reaction networks composition for molecular computations

Renlei Jiang, Yuzhen Fan, Di Fan +2

Molecular computation based on chemical reaction networks (CRNs) has emerged as a promising paradigm for designing programmable biochemical systems. However, the implementation of…

cs.LG2024

Explainable AI Integrated Feature Engineering for Wildfire Prediction

Di Fan, Ayan Biswas, James Paul Ahrens

Wildfires present intricate challenges for prediction, necessitating the use of sophisticated machine learning techniques for effective modeling\cite{jain2020review}. In our resear…

cs.CV2023

Biomedical image analysis competitions: The state of current participation practice

Matthias Eisenmann, Annika Reinke, Vivienn Weru +352

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…

eess.IV2022

GPU-Net: Lightweight U-Net with more diverse features

Heng Yu, Di Fan, Weihu Song

Image segmentation is an important task in the medical image field and many convolutional neural networks (CNNs) based methods have been proposed, among which U-Net and its variant…

cs.SI2026

Jointly Optimizing Debiased CTR and Uplift for Coupons Marketing: A Unified Causal Framework

Siyun Yang, Shixiao Yang, Jian Wang +6

In online advertising, marketing interventions such as coupons introduce significant confounding bias into Click-Through Rate (CTR) prediction. Observed clicks reflect a mixture of…

cs.CV2025

PDSE: A Multiple Lesion Detector for CT Images using PANet and Deformable Squeeze-and-Excitation Block

Di Fan, Heng Yu, Zhiyuan Xu

Detecting lesions in Computed Tomography (CT) scans is a challenging task in medical image processing due to the diverse types, sizes, and locations of lesions. Recently, various o…

cs.LG2024

Learning Network Representations with Disentangled Graph Auto-Encoder

Di Fan, Chuanhou Gao

The (variational) graph auto-encoder is widely used to learn representations for graph-structured data. However, the formation of real-world graphs is a complicated and heterogeneo…

cs.LG2023

Domain Knowledge integrated for Blast Furnace Classifier Design

Shaohan Chen, Di Fan, Chuanhou Gao

Blast furnace modeling and control is one of the important problems in the industrial field, and the black-box model is an effective mean to describe the complex blast furnace syst…

cs.DC2021

On the Fairness of Swarm Learning in Skin Lesion Classification

Di Fan, Yifan Wu, Xiaoxiao Li

in healthcare. However, the existing AI model may be biased in its decision marking. The bias induced by data itself, such as collecting data in subgroups only, can be mitigated by…

cond-mat.mtrl-sci2025

Unexpected Density Functional Dependence of the Antipolar Phase in HfO

Di Fan, Tianyuan Zhu, Shi Liu

The antipolar phase of HfO has been suggested to play an important role in the phase transition and polarization switching mechanisms in ferroelectric hafnia. In this st…

eess.SP2023

Human Emotion Recognition Based On Galvanic Skin Response signal Feature Selection and SVM

Di Fan, Mingyang Liu, Xiaohan Zhang +1

A novel human emotion recognition method based on automatically selected Galvanic Skin Response (GSR) signal features and SVM is proposed in this paper. GSR signals were acquired b…

physics.comp-ph2025

Rippled Moire Superlattices for Decoupled Ferroelectric Bits

Di Fan, Changming Ke, Shi Liu

Symmetry considerations suggest that moire superlattices formed by twisted two-dimensional materials should preserve overall inversion symmetry. However, experiments consistently r…

math.CA2023

Commutators for the maximal and sharp functions with weighted Lipschitz functions on weighted Morrey spaces

Pu Zhang, Di Fan

We study the boundedness of commutators of the Hardy-Littlewood maximal function and the sharp maximal function on weighted Morrey spaces when the symbols of the commutators belong…

cs.LG2025

Disentangled Graph Autoencoder for Treatment Effect Estimation

Di Fan, Renlei Jiang, Yunhao Wen +1

Treatment effect estimation from observational data has attracted significant attention across various research fields. However, many widely used methods rely on the unconfoundedne…

stat.ML2025

LILI clustering algorithm: Limit Inferior Leaf Interval Integrated into Causal Forest for Causal Interference

Yiran Dong, Di Fan, Chuanhou Gao

Causal forest methods are powerful tools in causal inference. Similar to traditional random forest in machine learning, causal forest independently considers each causal tree. Howe…

cond-mat.mes-hall2018

Inverse Spin Hall Effect Induced by Asymmetric Illumination of Light on Topological Insulator BiSe

Di Fan, Rei Hobara, Ryota Akiyama +1

Using circularly polarized light is an alternative to electronic ways for spin injection into materials. Spins are injected at a point of the light illumination, and then diffuse a…

cs.LG2024

Causal Flow-based Variational Auto-Encoder for Disentangled Causal Representation Learning

Di Fan, Yannian Kou, Chuanhou Gao

Disentangled representation learning aims to learn low-dimensional representations where each dimension corresponds to an underlying generative factor. While the Variational Auto-E…