Learning with Memory Embeddings. - Volker Tresp; Cristóbal Esteban; Yinchong Yang; Stephan Baier; Denis Krompaß (CoRR, 2015)

Embedding Mapping Approaches for Tensor Factorization and Knowledge Graph Modelling. - Yinchong Yang; Cristóbal Esteban; Volker Tresp (ESWC, 2016)

Predicting the co-evolution of event and Knowledge Graphs. - Cristóbal Esteban; Volker Tresp; Yinchong Yang; Stephan Baier; Denis Krompass (FUSION, 2016)

Predicting Clinical Events by Combining Static and Dynamic Information Using Recurrent Neural Networks. - Cristóbal Esteban; Oliver Staeck; Stephan Baier; Yinchong Yang; Volker Tresp (ICHI, 2016)

Predictive Clinical Decision Support System with RNN Encoding and Tensor Decoding. - Yinchong Yang; Peter A. Fasching; Markus Wallwiener; Tanja N. Fehm; Sara Y. Brucker; Volker Tresp (CoRR, 2016)

Embedding Learning for Declarative Memories. - Volker Tresp; Yunpu Ma; Stephan Baier; Yinchong Yang (ESWC (1), 2017)

Predictive Modeling of Therapy Decisions in Metastatic Breast Cancer with Recurrent Neural Network Encoder and Multinomial Hierarchical Regression Decoder. - Yinchong Yang; Peter A. Fasching; Volker Tresp (ICHI, 2017)

Tensor-Train Recurrent Neural Networks for Video Classification. - Yinchong Yang; Denis Krompass; Volker Tresp (ICML, 2017)

Modeling Progression Free Survival in Breast Cancer with Tensorized Recurrent Neural Networks and Accelerated Failure Time Models. - Yinchong Yang; Peter A. Fasching; Volker Tresp (MLHC, 2017)

Understanding Individual Decisions of CNNs via Contrastive Backpropagation. - Jindong Gu; Yinchong Yang; Volker Tresp (ACCV (3), 2018)

Explaining Therapy Predictions with Layer-Wise Relevance Propagation in Neural Networks. - Yinchong Yang; Volker Tresp; Marius Wunderle; Peter A. Fasching (ICHI, 2018)

Enhancing representation learning with tensor decompositions for knowledge graphs and high dimensional sequence modeling. - Yinchong Yang (2018)

Categorical EHR Imputation with Generative Adversarial Nets. - Yinchong Yang; Zhiliang Wu; Volker Tresp; Peter A. Fasching (ICHI, 2019)

Learning Individualized Treatment Rules with Estimated Translated Inverse Propensity Score. - Zhiliang Wu; Yinchong Yang; Yunpu Ma; Yushan Liu 002; Rui Zhao 011; Michael Moor; Volker Tresp (ICHI, 2020)

Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning. - Zhiliang Wu; Yinchong Yang; Jindong Gu; Volker Tresp (ICHI, 2021)

Uncertainty-Aware Time-to-Event Prediction using Deep Kernel Accelerated Failure Time Models. - Zhiliang Wu; Yinchong Yang; Peter A. Fasching; Volker Tresp (MLHC, 2021)

Multi-output Gaussian Processes for uncertainty-aware recommender systems. - Yinchong Yang; Florian Buettner 001 (UAI, 2021)

Facilitating Change Implementation for Continuous ML-Safety Assurance. - Chih-Hong Cheng; Nguyen Anh Vu Doan; Balahari Balu; Franziska Schwaiger; Emmanouil Seferis; Simon Burton 001; Yassine Qamsane; Ankit Shukla; Yinchong Yang; Zhiliang Wu; Andreas Hapfelmeier; Ingo Thon (CoRR, 2022)

Data-driven Verification of DNNs for Object Recognition. - Clemens Otte; Yinchong Yang; Danny Benlin Oswan (CoRR, 2024)