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11/24/2022
Trust Your ∇: Gradient-based Intervention Targeting for Causal Discovery
Inferring causal structure from data is a challenging task of fundamenta...
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11/07/2022
FED-CD: Federated Causal Discovery from Interventional and Observational Data
Causal discovery, the inference of causal relations from data, is a core...
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08/19/2022
Predicting the protein-ligand affinity from molecular dynamics trajectories
The accurate protein-ligand binding affinity prediction is essential in ...
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10/07/2021
Boxhead: A Dataset for Learning Hierarchical Representations
Disentanglement is hypothesized to be beneficial towards a number of dow...
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09/06/2021
Learning Neural Causal Models with Active Interventions
Discovering causal structures from data is a challenging inference probl...
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02/22/2021
Towards Causal Representation Learning
The two fields of machine learning and graphical causality arose and dev...
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06/14/2020
Structural Autoencoders Improve Representations for Generation and Transfer
We study the problem of structuring a learned representation to signific...
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11/29/2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
In recent years, the interest in unsupervised learning of disentangled r...
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10/31/2018
