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09/01/2023
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark
The recent Long-Range Graph Benchmark (LRGB, Dwivedi et al. 2022) introd...
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01/27/2023
AdaBoost is not an Optimal Weak to Strong Learner
AdaBoost is a classic boosting algorithm for combining multiple inaccura...
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06/03/2022
Optimal Weak to Strong Learning
The classic algorithm AdaBoost allows to convert a weak learner, that is...
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06/01/2022
Graph Machine Learning for Design of High-Octane Fuels
Fuels with high-knock resistance enable modern spark-ignition engines to...
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02/24/2021
On the Parameterized Complexity of Learning Logic
We analyse the complexity of learning first-order definable concepts in ...
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02/17/2021
Graph Learning with 1D Convolutions on Random Walks
We propose CRaWl (CNNs for Random Walks), a novel neural network archite...
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05/20/2020
The Effects of Randomness on the Stability of Node Embeddings
We systematically evaluate the (in-)stability of state-of-the-art node e...
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09/24/2019
Learning definable hypotheses on trees
We study the problem of learning properties of nodes in tree structures....
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09/18/2019
RUN-CSP: Unsupervised Learning of Message Passing Networks for Binary Constraint Satisfaction Problems
Constraint satisfaction problems form an important and wide class of com...
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10/04/2018