Search Results for author: Jun Bai

Found 7 papers, 5 papers with code

Unsupversied feature correlation model to predict breast abnormal variation maps in longitudinal mammograms

1 code implementation28 Dec 2023 Jun Bai, Annie Jin, Madison Adams, Clifford Yang, Sheida Nabavi

In this study, we focus on improving the early detection and accurate diagnosis of breast abnormalities, which is crucial for improving patient outcomes and reducing the mortality rate of breast cancer.

Anomaly Detection Feature Correlation +1

Improving Variational Autoencoders with Density Gap-based Regularization

1 code implementation1 Nov 2022 Jianfei Zhang, Jun Bai, Chenghua Lin, Yanmeng Wang, Wenge Rong

There are effective ways proposed to prevent posterior collapse in VAEs, but we observe that they in essence make trade-offs between posterior collapse and hole problem, i. e., mismatch between the aggregated posterior distribution and the prior distribution.

Language Modelling Representation Learning

Enhancing Dual-Encoders with Question and Answer Cross-Embeddings for Answer Retrieval

no code implementations Findings (EMNLP) 2021 Yanmeng Wang, Jun Bai, Ye Wang, Jianfei Zhang, Wenge Rong, Zongcheng Ji, Shaojun Wang, Jing Xiao

To keep independent encoding of questions and answers during inference stage, variational auto-encoder is further introduced to reconstruct answers (questions) from question (answer) embeddings as an auxiliary task to enhance QA interaction in representation learning in training stage.

Question Answering Representation Learning +2

Semantic Labeling in Very High Resolution Images via a Self-Cascaded Convolutional Neural Network

1 code implementation30 Jul 2018 Yongcheng Liu, Bin Fan, Lingfeng Wang, Jun Bai, Shiming Xiang, Chunhong Pan

Specifically, for confusing manmade objects, ScasNet improves the labeling coherence with sequential global-to-local contexts aggregation.

Multi-ary Pulse Amplitude Modulated Signal Processing Using Bistable Stochastic Resonance

no code implementations International Conference on Noise and Fluctuations (ICNF) 2015 Jin Liu, Zan Li, Rui Gao, Jun Bai, Linlin Liang

On this basis, the mechanism of the BSR system response to MPAM signal inputs is elucidated, and a corresponding decoding scheme is proposed.

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