3 citations · 4 across the 7 of their papers we have counts for
7 papers
ScDiVa: Masked Discrete Diffusion for Joint Modeling of Single-Cell Identity and Expression
Mingxuan Wang, Cheng Chen, Gaoyang Jiang +4
Single-cell RNA-seq profiles are high-dimensional, sparse, and unordered, causing autoregressive generation to impose an artificial ordering bias and suffer from error accumulation…
Unleashing the Power of Image-Tabular Self-Supervised Learning via Breaking Cross-Tabular Barriers
Yibing Fu, Yunpeng Zhao, Zhitao Zeng +2
Multi-modal learning integrating medical images and tabular data has significantly advanced clinical decision-making in recent years. Self-Supervised Learning (SSL) has emerged as…
Generalized Category Discovery via Token Manifold Capacity Learning
Luyao Tang, Kunze Huang, Chaoqi Chen +1
Generalized category discovery (GCD) is essential for improving deep learning models' robustness in open-world scenarios by clustering unlabeled data containing both known and nove…
EigenGS Representation: From Eigenspace to Gaussian Image Space
Lo-Wei Tai, Ching-En Li, Cheng-Lin Chen +3
Principal Component Analysis (PCA), a classical dimensionality reduction technique, and 2D Gaussian representation, an adaptation of 3D Gaussian Splatting for image representation,…
Low-Bitwidth Floating Point Quantization for Efficient High-Quality Diffusion Models
Cheng Chen, Christina Giannoula, Andreas Moshovos
Diffusion models are emerging models that generate images by iteratively denoising random Gaussian noise using deep neural networks. These models typically exhibit high computation…
Dealing with All-stage Missing Modality: Towards A Universal Model with Robust Reconstruction and Personalization
Yunpeng Zhao, Cheng Chen, Qing You Pang +4
Addressing missing modalities presents a critical challenge in multimodal learning. Current approaches focus on developing models that can handle modality-incomplete inputs during…
Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization
Hongzheng Yang, Cheng Chen, Yueyao Chen +3
Uncertainty estimation plays an important role for future reliable deployment of deep segmentation models in safety-critical scenarios such as medical applications. However, existi…