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01/04/2023
Evaluation of Induced Expert Knowledge in Causal Structure Learning by NOTEARS
Causal modeling provides us with powerful counterfactual reasoning and i...
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01/04/2023
Machine Fault Classification using Hamiltonian Neural Networks
A new approach is introduced to classify faults in rotating machinery ba...
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11/08/2022
From Causal Pairs to Causal Graphs
Causal structure learning from observational data remains a non-trivial ...
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02/12/2020
Explainable Deep Modeling of Tabular Data using TableGraphNet
The vast majority of research on explainability focuses on post-explaina...
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10/21/2019
Approximate Sampling using an Accelerated Metropolis-Hastings based on Bayesian Optimization and Gaussian Processes
Markov Chain Monte Carlo (MCMC) methods have a drawback when working wit...
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10/01/2019
A Multiple Filter Based Neural Network Approach to the Extrapolation of Adsorption Energies on Metal Surfaces for Catalysis Applications
Computational catalyst discovery involves the development of microkineti...
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12/23/2017
An Approximate Bayesian Long Short-Term Memory Algorithm for Outlier Detection
Long Short-Term Memory networks trained with gradient descent and back-p...
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08/08/2017
