Publications (28)
Conditional neural field for spatial dimension reduction of turbulence data: a comparison study
Junyi Guo, Pan Du, Xiantao Fan +2
We investigate conditional neural fields (CNFs), mesh-agnostic, coordinate-based decoders conditioned on a low-dimensional latent, for spatial dimensionality reduction of turbulent…
Personalized Clustering via Targeted Representation Learning
Xiwen Geng, Suyun Zhao, Yixin Yu +5
Clustering traditionally aims to reveal a natural grouping structure within unlabeled data. However, this structure may not always align with users' preferences. In this paper, we…
DiFVM: A Vectorized Graph-Based Finite Volume Solver for Differentiable CFD on Unstructured Meshes
Pan Du, Yongqi Li, Mingqi Xu +1
Differentiable programming has emerged as a structural prerequisite for gradient-based inverse problems and end-to-end hybrid physics--machine learning in computational fluid dynam…
Hierarchical LoG Bayesian Neural Network for Enhanced Aorta Segmentation
Delin An, Pan Du, Pengfei Gu +2
Accurate segmentation of the aorta and its associated arch branches is crucial for diagnosing aortic diseases. While deep learning techniques have significantly improved aorta segm…
Meta-Learning for Neural Relation Classification with Distant Supervision
Zhenzhen Li, Jian-Yun Nie, Benyou Wang +4
Distant supervision provides a means to create a large number of weakly labeled data at low cost for relation classification. However, the resulting labeled instances are very nois…
Batched Self-Consistency Improves LLM Relevance Assessment and Ranking
Anton Korikov, Pan Du, Scott Sanner +1
LLM query-passage relevance assessment is typically studied using a one-by-one pointwise (PW) strategy where each LLM call judges one passage at a time. However, this strategy requ…