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1
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
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The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations

Computer graphics forum, 2020-06, Vol.39 (3), p.713-756 [Peer Reviewed Journal]

Attribution ;ISSN: 0167-7055 ;EISSN: 1467-8659 ;DOI: 10.1111/cgf.14034

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2
A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI
A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI
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A Survey on Explainable Artificial Intelligence (XAI): Toward Medical XAI

IEEE transaction on neural networks and learning systems, 2021-11, Vol.32 (11), p.4793-4813

ISSN: 2162-237X ;EISSN: 2162-2388 ;DOI: 10.1109/TNNLS.2020.3027314 ;PMID: 33079674 ;CODEN: ITNNAL

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3
CC2Vec: Distributed Representations of Code Changes
CC2Vec: Distributed Representations of Code Changes
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Conference Proceeding 		Add to My Research

CC2Vec: Distributed Representations of Code Changes

Distributed under a Creative Commons Attribution 4.0 International License ;DOI: 10.1145/3377811.3380361

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4
In AI, is bigger always better?
In AI, is bigger always better?
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In AI, is bigger always better?

Nature (London), 2023-03, Vol.615 (7951), p.202-205 [Peer Reviewed Journal]

ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/d41586-023-00641-w ;PMID: 36890378

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5
Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron model
Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron model
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Landslide susceptibility prediction based on a semi-supervised multiple-layer perceptron model

Landslides, 2020-12, Vol.17 (12), p.2919-2930 [Peer Reviewed Journal]

Springer-Verlag GmbH Germany, part of Springer Nature 2020 ;Springer-Verlag GmbH Germany, part of Springer Nature 2020. ;ISSN: 1612-510X ;EISSN: 1612-5118 ;DOI: 10.1007/s10346-020-01473-9

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6
Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python
Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python
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Conference Proceeding 		Add to My Research

Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE), 2022, p.2241-2252

EISSN: 1558-1225 ;EISBN: 9781450392211 ;EISBN: 1450392210 ;DOI: 10.1145/3510003.3510124 ;CODEN: IEEPAD

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7
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
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Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

IEEE access, 2018-01, Vol.6, p.52138-52160 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2018.2870052 ;CODEN: IAECCG

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8
Explainable Machine Learning for Scientific Insights and Discoveries
Explainable Machine Learning for Scientific Insights and Discoveries
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Explainable Machine Learning for Scientific Insights and Discoveries

IEEE access, 2020, Vol.8, p.42200-42216 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2020.2976199 ;CODEN: IAECCG

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9
Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method
Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method
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Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method

Journal of computational physics, 2021-11, Vol.445 [Peer Reviewed Journal]

ISSN: 0021-9991 ;ISSN: 1090-2716 ;EISSN: 1090-2716 ;DOI: 10.1016/j.jcp.2021.110624

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10
Neural Program Repair with Execution-based Backpropagation
Neural Program Repair with Execution-based Backpropagation
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Conference Proceeding 		Add to My Research

Neural Program Repair with Execution-based Backpropagation

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE), 2022, p.1506-1518

EISSN: 1558-1225 ;EISBN: 9781450392211 ;EISBN: 1450392210 ;DOI: 10.1145/3510003.3510222 ;CODEN: IEEPAD

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11
Computation reuse in DNNs by exploiting input similarity
Computation reuse in DNNs by exploiting input similarity
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Conference Proceeding 		Add to My Research

Computation reuse in DNNs by exploiting input similarity

info:eu-repo/semantics/openAccess ;ISBN: 1538659859 ;ISBN: 9781538659854 ;DOI: 10.1109/ISCA.2018.00016

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12
VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization
VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization
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Article 		Add to My Research

VisEvol: Visual Analytics to Support Hyperparameter Search through Evolutionary Optimization

Computer graphics forum, 2021-06, Vol.40 (3), p.201 [Peer Reviewed Journal]

ISSN: 0167-7055 ;ISSN: 1467-8659 ;EISSN: 1467-8659 ;DOI: 10.1111/cgf.14300

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13
Synthetic data in machine learning for medicine and healthcare
Synthetic data in machine learning for medicine and healthcare
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Article 		Add to My Research

Synthetic data in machine learning for medicine and healthcare

Nature biomedical engineering, 2021-06, Vol.5 (6), p.493-497 [Peer Reviewed Journal]

Springer Nature Limited 2021. ;ISSN: 2157-846X ;EISSN: 2157-846X ;DOI: 10.1038/s41551-021-00751-8 ;PMID: 34131324

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14
The Matthews Correlation Coefficient (MCC) is More Informative Than Cohen's Kappa and Brier Score in Binary Classification Assessment
The Matthews Correlation Coefficient (MCC) is More Informative Than Cohen's Kappa and Brier Score in Binary Classification Assessment
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The Matthews Correlation Coefficient (MCC) is More Informative Than Cohen's Kappa and Brier Score in Binary Classification Assessment

IEEE access, 2021, Vol.9, p.78368-78381 [Peer Reviewed Journal]

Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021 ;ISSN: 2169-3536 ;EISSN: 2169-3536 ;DOI: 10.1109/ACCESS.2021.3084050 ;CODEN: IAECCG

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15
Optimization with Sparsity-Inducing Penalties
Optimization with Sparsity-Inducing Penalties
Material Type:
Book 		Add to My Research

Optimization with Sparsity-Inducing Penalties

Foundations and trends in machine learning, 2012 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1935-8237 ;EISSN: 1935-8245 ;DOI: 10.1561/2200000015

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16
Deep learning in spiking neural networks
Deep learning in spiking neural networks
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Article 		Add to My Research

Deep learning in spiking neural networks

Neural networks, 2019-03, Vol.111, p.47-63 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0893-6080 ;EISSN: 1879-2782 ;DOI: 10.1016/j.neunet.2018.12.002

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17
How to make driverless cars safer - expose them to lots of dangerous drivers
How to make driverless cars safer - expose them to lots of dangerous drivers
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Article 		Add to My Research

How to make driverless cars safer - expose them to lots of dangerous drivers

Nature (London), 2023-03 [Peer Reviewed Journal]

ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/d41586-023-00867-8 ;PMID: 36949133

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18
Machine Learning in High Energy Physics Community White Paper
Machine Learning in High Energy Physics Community White Paper
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Machine Learning in High Energy Physics Community White Paper

Journal of physics. Conference series, 2018-09, Vol.1085 (2), p.22008 [Peer Reviewed Journal]

Published under licence by IOP Publishing Ltd ;2018. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1742-6588 ;ISSN: 1742-6596 ;EISSN: 1742-6596 ;DOI: 10.1088/1742-6596/1085/2/022008

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19
ECNN: evaluating a cluster-neural network model for city innovation capability
ECNN: evaluating a cluster-neural network model for city innovation capability
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Article 		Add to My Research

ECNN: evaluating a cluster-neural network model for city innovation capability

Neural computing & applications, 2022-08, Vol.34 (15), p.12331-12343 [Peer Reviewed Journal]

The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021 ;The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2021. ;ISSN: 0941-0643 ;EISSN: 1433-3058 ;DOI: 10.1007/s00521-021-06471-z

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20
Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning
Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning
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Article 		Add to My Research

Privacy Preserving Machine Learning with Homomorphic Encryption and Federated Learning

Future internet, 2021-04, Vol.13 (4), p.94 [Peer Reviewed Journal]

2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1999-5903 ;EISSN: 1999-5903 ;DOI: 10.3390/fi13040094

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