truth_inference_with_neural_network

tensorflow-gpu==2.6.0

Neural Network

1. AggNet (AggNet: Deep Learning From Crowds for Mitosis Detection in Breast Cancer Histology Images): Paper(https://ieeexplore.ieee.org/document/7405343). Source code(https://github.com/fmpr/CrowdLayer).
2. LFC (Deep Learning from Crowds): Paper(https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/16102; https://arxiv.org/abs/1709.01779). Source code(https://github.com/fmpr/CrowdLayer).
3. SpeeLFC (Structured Probabilistic End-to-End Learning from Crowds): Paper(https://www.ijcai.org/proceedings/2020/210). Source code(Unavailable).
4. CoNAL (Learning from Crowds by Modeling Common Confusions): Paper(https://ojs.aaai.org/index.php/AAAI/article/view/16730). Source code(https://github.com/zdchu/CoNAL, https://github.com/seunghyukcho/CoNAL-pytorch).
5. MAX-MIG (Max-MIG: an Information Theoretic Approach for Joint Learning from Crowds): Paper(https://openreview.net/forum?id=BJg9DoR9t7). Source code(https://github.com/Newbeeer/Max-MIG).