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Learning to Explain Graph Neural Networks


Sep 28, 2022
Giuseppe Serra, Mathias Niepert


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Adaptive Perturbation-Based Gradient Estimation for Discrete Latent Variable Models


Sep 11, 2022
Pasquale Minervini, Luca Franceschi, Mathias Niepert

* arXiv admin note: text overlap with arXiv:2106.01798 

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Ordered Subgraph Aggregation Networks


Jun 28, 2022
Chendi Qian, Gaurav Rattan, Floris Geerts, Christopher Morris, Mathias Niepert

* Fixed link to code repository 

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Integrating diverse extraction pathways using iterative predictions for Multilingual Open Information Extraction


Oct 15, 2021
Bhushan Kotnis, Kiril Gashteovski, Carolin Lawrence, Daniel Oñoro Rubio, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert


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AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark


Sep 15, 2021
Niklas Friedrich, Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavaš


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BenchIE: Open Information Extraction Evaluation Based on Facts, Not Tokens


Sep 14, 2021
Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Goran Glavas, Mathias Niepert


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VEGN: Variant Effect Prediction with Graph Neural Networks


Jun 25, 2021
Jun Cheng, Carolin Lawrence, Mathias Niepert

* Accepted at Workshop on Computational Biology, co-located with the 38th International Conference on Machine Learning 

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Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions


Jun 03, 2021
Mathias Niepert, Pasquale Minervini, Luca Franceschi


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Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs


Nov 24, 2020
Cheng Wang, Carolin Lawrence, Mathias Niepert


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