E-LIB Suche - Ergebnisse für: Mowbray, Max

1

Constructing a Symbolic Regression-Based Interpretable Soft..:

Kay, Harry ; Kay, Sam ; Mowbray, Max...
Industrial & Engineering Chemistry Research. 63 (2024) 9 - p. 4083-4092 , 2024

Link: https://doi.org/10.1021/..

2

An analysis of multi-agent reinforcement learning for decen..:

Mousa, Marwan ; van de Berg, Damien ; Kotecha, Niki..
Computers & Chemical Engineering. 188 (2024) - p. 108783 , 2024

Link: https://doi.org/10.1016/..

3

Integrating transfer learning within data-driven soft senso..:

Kay, Sam ; Kay, Harry ; Mowbray, Max...
Digital Chemical Engineering. 10 (2024) - p. 100142 , 2024

Link: https://doi.org/10.1016/..

4

Distributional reinforcement learning for inventory managem..:

Wu, Guoquan ; de Carvalho Servia, Miguel Ángel ; Mowbray, Max
Digital Chemical Engineering. 6 (2023) - p. 100073 , 2023

Link: https://doi.org/10.1016/..

5

Integrating Autoencoder and Heteroscedastic Noise Neural Ne..:

Kay, Sam ; Kay, Harry ; Mowbray, Max...
Industrial & Engineering Chemistry Research. 61 (2022) 36 - p. 13559-13569 , 2022

Link: https://doi.org/10.1021/..

6

Integrating process design and control using reinforcement ..:

Sachio, Steven ; Mowbray, Max ; Papathanasiou, Maria M...
Chemical Engineering Research and Design. 183 (2022) - p. 160-169 , 2022

Link: https://doi.org/10.1016/..

7

Industrial data science – a review of machine learning appl..:

Mowbray, Max ; Vallerio, Mattia ; Perez-Galvan, Carlos...
Reaction Chemistry & Engineering. 7 (2022) 7 - p. 1471-1509 , 2022

Link: https://doi.org/10.1039/..

8

Using process data to generate an optimal control policy vi..:

Mowbray, Max ; Smith, Robin ; Del Rio‐Chanona, Ehecatl A..
AIChE Journal. 67 (2021) 9 - p. , 2021

Link: https://doi.org/10.1002/..

9

A two-step multivariate statistical learning approach for b..:

Hicks, Aaron ; Johnston, Matthew ; Mowbray, Max...
Digital Chemical Engineering. 1 (2021) - p. 100003 , 2021

Link: https://doi.org/10.1016/..

10

Constrained model-free reinforcement learning for process o..:

Pan, Elton ; Petsagkourakis, Panagiotis ; Mowbray, Max..
Computers & Chemical Engineering. 154 (2021) - p. 107462 , 2021

Link: https://doi.org/10.1016/..

11

Development and Characterization of a Probe Device toward I..:

Mowbray, Max ; Banbury, Carl ; Rickard, Jonathan J. S...
ACS Biomaterials Science & Engineering. 7 (2021) 3 - p. 1252-1262 , 2021

Link: https://doi.org/10.1021/..

12

Generating an optimal control policy via apprenticeship and..:

, In: 31st European Symposium on Computer Aided Process Engineering; Computer Aided Chemical Engineering,

Mowbray, Max ; Smith, Robin ; Chanona, Antonio Del Río. - p. 1215-1220 , 2021

Link: https://doi.org/10.1016/..

13

Machine learning for biochemical engineering: A review:

Mowbray, Max ; Savage, Thomas ; Wu, Chufan...
Biochemical Engineering Journal. 172 (2021) - p. 108054 , 2021

Link: https://doi.org/10.1016/..

14

A reinforcement learning‐based hybrid modeling framework fo..:

Mowbray, Max R. ; Wu, Chufan ; Rogers, Alexander W...
Biotechnology and Bioengineering. 120 (2022) 1 - p. 154-168 , 2022

Link: https://doi.org/10.1002/..

15

An Analysis of Multi-Agent Reinforcement Learning for Decen..:

Mousa, Marwan ; van de Berg, Damien ; Kotecha, Niki..
http://arxiv.org/abs/2307.11432. , 2023

Link: http://arxiv.org/abs/230..