Alex Aussem

874 total citations
25 papers, 501 citations indexed

About

Alex Aussem is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Alex Aussem has authored 25 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 5 papers in Molecular Biology. Recurrent topics in Alex Aussem's work include Neural Networks and Applications (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Machine Learning and Data Classification (5 papers). Alex Aussem is often cited by papers focused on Neural Networks and Applications (6 papers), Bayesian Modeling and Causal Inference (5 papers) and Machine Learning and Data Classification (5 papers). Alex Aussem collaborates with scholars based in France, United Kingdom and United States. Alex Aussem's co-authors include Haytham Elghazel, Fionn Murtagh, Maxime Gasse, M. Sarazin, Fionn Murtagh, David A. Hill, David R.C. Hill, André Tchernof, Sophie Rome and Antoine Mahul and has published in prestigious journals such as Expert Systems with Applications, BMC Bioinformatics and Neural Computation.

In The Last Decade

Alex Aussem

25 papers receiving 468 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Alex Aussem France 14 299 104 63 56 55 25 501
Yunjie Zhang China 6 248 0.8× 131 1.3× 49 0.8× 73 1.3× 31 0.6× 25 513
Haitao Lin China 12 238 0.8× 95 0.9× 76 1.2× 45 0.8× 20 0.4× 36 522
I. Cloete South Africa 12 303 1.0× 61 0.6× 46 0.7× 32 0.6× 23 0.4× 37 504
Alireza Farhangfar Canada 6 276 0.9× 75 0.7× 47 0.7× 66 1.2× 27 0.5× 8 478
Yangguang Liu China 11 220 0.7× 96 0.9× 26 0.4× 63 1.1× 28 0.5× 52 468
Xuewen Chen United States 8 357 1.2× 99 1.0× 31 0.5× 27 0.5× 71 1.3× 19 507
Hanen Borchani Spain 6 200 0.7× 85 0.8× 27 0.4× 27 0.5× 38 0.7× 8 506
M. Carmen Garrido Spain 9 227 0.8× 63 0.6× 35 0.6× 26 0.5× 32 0.6× 34 402
Stanley A. Shanies United States 5 342 1.1× 152 1.5× 49 0.8× 107 1.9× 28 0.5× 6 632
Robert E. Banfield United States 8 323 1.1× 104 1.0× 15 0.2× 49 0.9× 34 0.6× 12 514

Countries citing papers authored by Alex Aussem

Since Specialization
Citations

This map shows the geographic impact of Alex Aussem's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alex Aussem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex Aussem more than expected).

Fields of papers citing papers by Alex Aussem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alex Aussem. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alex Aussem. The network helps show where Alex Aussem may publish in the future.

Co-authorship network of co-authors of Alex Aussem

This figure shows the co-authorship network connecting the top 25 collaborators of Alex Aussem. A scholar is included among the top collaborators of Alex Aussem based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alex Aussem. Alex Aussem is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Aussem, Alex, et al.. (2019). Hierarchical Recurrent Attention Networks for Context-Aware Education Chatbots. SPIRE - Sciences Po Institutional REpository. 1–8. 4 indexed citations
2.
Aussem, Alex, et al.. (2018). On the use of binary stochastic autoencoders for multi-label classification under the zero-one loss. Procedia Computer Science. 144. 71–80. 1 indexed citations
3.
Elghazel, Haytham, et al.. (2016). An extensive empirical comparison of ensemble learning methods for binary classification. Pattern Analysis and Applications. 19(4). 1093–1128. 13 indexed citations
4.
Prestat, Emmanuel, Julie A. Vendrell, Aurélie Thollet, et al.. (2013). Learning the local Bayesian network structure around the ZNF217 oncogene in breast tumours. Computers in Biology and Medicine. 43(4). 334–341. 7 indexed citations
5.
Elghazel, Haytham & Alex Aussem. (2013). Unsupervised feature selection with ensemble learning. Machine Learning. 98(1-2). 157–180. 59 indexed citations
6.
Elghazel, Haytham, et al.. (2012). A semi-supervised feature ranking method with ensemble learning. Pattern Recognition Letters. 33(10). 1426–1433. 37 indexed citations
7.
Elghazel, Haytham, et al.. (2011). Semi-supervised Feature Importance Evaluation with Ensemble Learning. 31–40. 13 indexed citations
8.
Aussem, Alex, et al.. (2010). Analysis of lifestyle and metabolic predictors of visceral obesity with Bayesian Networks. BMC Bioinformatics. 11(1). 487–487. 11 indexed citations
9.
Aussem, Alex, et al.. (2009). A novel Markov boundary based feature subset selection algorithm. Neurocomputing. 73(4-6). 578–584. 18 indexed citations
10.
Aussem, Alex, et al.. (2009). A conservative feature subset selection algorithm with missing data. Neurocomputing. 73(4-6). 585–590. 20 indexed citations
11.
Mahul, Antoine & Alex Aussem. (2003). Distributed Neural Networks for Quality of Service Estimation in Communication Networks. International Journal of Computational Intelligence and Applications. 3(3). 297–308. 3 indexed citations
12.
Aussem, Alex. (2002). Sufficient Conditions for Error Backflow Convergence in Dynamical Recurrent Neural Networks. Neural Computation. 14(8). 1907–1927. 6 indexed citations
13.
Aussem, Alex & Fionn Murtagh. (2001). Web traffic demand forecasting using wavelet‐based multiscale decomposition. International Journal of Intelligent Systems. 16(2). 215–236. 18 indexed citations
14.
Aussem, Alex & Fionn Murtagh. (2001). Web traffic demand forecasting using wavelet‐based multiscale decomposition. International Journal of Intelligent Systems. 16(2). 215–236. 1 indexed citations
15.
Aussem, Alex & David R.C. Hill. (1999). Wedding connectionist and algorithmic modelling towards forecasting Caulerpa taxifolia development in the north-western Mediterranean sea. Ecological Modelling. 120(2-3). 225–236. 7 indexed citations
16.
Aussem, Alex. (1999). Dynamical recurrent neural networks towards prediction and modeling of dynamical systems. Neurocomputing. 28(1-3). 207–232. 39 indexed citations
17.
Aussem, Alex & Fionn Murtagh. (1997). Combining Neural Network Forecasts on Wavelet-transformed Time Series. Connection Science. 9(1). 113–122. 72 indexed citations
18.
Aussem, Alex, Fionn Murtagh, & M. Sarazin. (1996). Fuzzy astronomical seeing nowcasts with a dynamical and recurrent connectionist network. Neurocomputing. 13(2-4). 359–373. 1 indexed citations
19.
Aussem, Alex, Fionn Murtagh, & M. Sarazin. (1995). DYNAMICAL RECURRENT NEURAL NETWORKS — TOWARDS ENVIRONMENTAL TIME SERIES PREDICTION. International Journal of Neural Systems. 6(2). 145–170. 30 indexed citations
20.
Murtagh, Fionn, Alex Aussem, & M. Sarazin. (1995). Nowcasting Astronomical Seeing: Towards an Operational Approach. Publications of the Astronomical Society of the Pacific. 107. 702–702. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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