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06/22/2023
Evolving Computation Graphs
Graph neural networks (GNNs) have demonstrated success in modeling relat...
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06/06/2023
How does over-squashing affect the power of GNNs?
Graph Neural Networks (GNNs) are the state-of-the-art model for machine ...
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02/09/2023
Equivariant MuZero
Deep reinforcement learning repeatedly succeeds in closed, well-defined ...
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11/29/2022
Continuous Neural Algorithmic Planners
Neural algorithmic reasoning studies the problem of learning algorithms ...
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10/06/2022
Expander Graph Propagation
Deploying graph neural networks (GNNs) on whole-graph classification or ...
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09/22/2022
A Generalist Neural Algorithmic Learner
The cornerstone of neural algorithmic reasoning is the ability to solve ...
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10/26/2021
How to transfer algorithmic reasoning knowledge to learn new algorithms?
Learning to execute algorithms is a fundamental problem that has been wi...
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10/11/2021
Neural Algorithmic Reasoners are Implicit Planners
Implicit planning has emerged as an elegant technique for combining lear...
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07/20/2021
Large-scale graph representation learning with very deep GNNs and self-supervision
Effectively and efficiently deploying graph neural networks (GNNs) at sc...
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05/31/2021
Neural message passing for joint paratope-epitope prediction
Antibodies are proteins in the immune system which bind to antigens to d...
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10/25/2020
XLVIN: eXecuted Latent Value Iteration Nets
Value Iteration Networks (VINs) have emerged as a popular method to inco...
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09/26/2020
Graph neural induction of value iteration
Many reinforcement learning tasks can benefit from explicit planning bas...
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05/02/2019
Drug-Drug Adverse Effect Prediction with Graph Co-Attention
Complex or co-existing diseases are commonly treated using drug combinat...
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06/12/2018
