Andrew D. Back

4.8k total citations · 1 hit paper
42 papers, 2.9k citations indexed

About

Andrew D. Back is a scholar working on Artificial Intelligence, Signal Processing and Control and Systems Engineering. According to data from OpenAlex, Andrew D. Back has authored 42 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 19 papers in Signal Processing and 11 papers in Control and Systems Engineering. Recurrent topics in Andrew D. Back's work include Neural Networks and Applications (30 papers), Blind Source Separation Techniques (18 papers) and Control Systems and Identification (8 papers). Andrew D. Back is often cited by papers focused on Neural Networks and Applications (30 papers), Blind Source Separation Techniques (18 papers) and Control Systems and Identification (8 papers). Andrew D. Back collaborates with scholars based in Australia, Japan and United States. Andrew D. Back's co-authors include Ah Chung Tsoi, C. Lee Giles, Sandra Lawrence, Thomas Trappenberg, Steve Lawrence, Nicolangelo Iannella, Tianping Chen, Jie Ouyang, Janet Wiles and Eric A. Wan and has published in prestigious journals such as IEEE Transactions on Signal Processing, Neural Computation and Neurocomputing.

In The Last Decade

Andrew D. Back

39 papers receiving 2.7k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Face recognition: a convolutional neural-network approach

1997 2.1k citations Sandra Lawrence, C. Lee Giles et al. IEEE Transactions on Neural Networks profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Andrew D. Back	1.1k	1.1k	490	375	336	42	2.9k
Y. Le Cun	1.4k 1.3×	1.4k 1.3×	297 0.6×	225 0.6×	266 0.8×	38	2.9k
N.B. Karayiannis	1.1k 1.0×	693 0.6×	353 0.7×	347 0.9×	235 0.7×	98	2.3k
P. A. Estévez	1.4k 1.2×	923 0.9×	394 0.8×	243 0.6×	358 1.1×	131	3.5k
Tapani Raiko	1.5k 1.3×	1.2k 1.1×	350 0.7×	216 0.6×	221 0.7×	61	3.2k
David B. Rosen	2.1k 1.8×	731 0.7×	316 0.6×	429 1.1×	252 0.8×	20	3.3k
Tom White	855 0.8×	987 0.9×	232 0.5×	189 0.5×	248 0.7×	7	2.9k
Jérôme Louradour	2.1k 1.8×	1.6k 1.5×	337 0.7×	267 0.7×	164 0.5×	27	3.7k
Mohamed Deriche	519 0.5×	1.3k 1.2×	401 0.8×	257 0.7×	314 0.9×	246	3.1k
James Martens	2.0k 1.8×	1.3k 1.2×	394 0.8×	171 0.5×	308 0.9×	23	3.5k
John S. Denker	2.6k 2.3×	2.1k 2.0×	441 0.9×	358 1.0×	395 1.2×	20	4.8k

Countries citing papers authored by Andrew D. Back

Since Specialization

Citations

This map shows the geographic impact of Andrew D. Back'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 Andrew D. Back with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew D. Back more than expected).

Fields of papers citing papers by Andrew D. Back

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew D. Back. 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 Andrew D. Back. The network helps show where Andrew D. Back may publish in the future.

Co-authorship network of co-authors of Andrew D. Back

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew D. Back. A scholar is included among the top collaborators of Andrew D. Back 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 Andrew D. Back. Andrew D. Back is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Back, Andrew D. & Janet Wiles. (2022). An Information Theoretic Approach to Symbolic Learning in Synthetic Languages. Entropy. 24(2). 259–259. 1 indexed citations

Back, Andrew D. & Ah Chung Tsoi. (2003). Nonlinear system identification using multilayer perceptrons with locally recurrent synaptic structure. 444–453. 2 indexed citations

Back, Andrew D. & Ah Chung Tsoi. (2003). Internal representation of data in multilayer perceptrons with IIR synapses. 1. 363–366. 1 indexed citations

Back, Andrew D. & Andreas S. Weigend. (2002). What drives stock returns?-an independent component analysis. xii. 141–156. 2 indexed citations

Back, Andrew D. & Ah Chung Tsoi. (2002). Alternative discrete-time operators in neural networks for nonlinear prediction. 4. 14–17. 1 indexed citations

Back, Andrew D. & Ah Chung Tsoi. (2002). Blind deconvolution of signals using a complex recurrent network. 565–574. 17 indexed citations

Iannella, Nicolangelo & Andrew D. Back. (2001). A spiking neural network architecture for nonlinear function approximation. Neural Networks. 14(6-7). 933–939. 33 indexed citations

Back, Andrew D. & Thomas Trappenberg. (2001). Selecting inputs for modeling using normalized higher order statistics and independent component analysis. IEEE Transactions on Neural Networks. 12(3). 612–617. 38 indexed citations

Back, Andrew D. & Tianping Chen. (1997). Approximation of Hybrid Systems by Neural Networks.. International Conference on Neural Information Processing. 326–329. 6 indexed citations

10.

Back, Andrew D. & Andrzej Cichocki. (1997). Blind Source Separation and Deconvolution of Fast Sampled Signals. International Conference on Neural Information Processing. 637–640. 1 indexed citations

11.

Tsoi, Ah Chung & Andrew D. Back. (1997). Discrete time recurrent neural network architectures: A unifying review. Neurocomputing. 15(3-4). 183–223. 83 indexed citations

12.

Lawrence, Sandra, Andrew D. Back, Ah Chung Tsoi, & C. Lee Giles. (1997). On the distribution of performance from multiple neural-network trials. IEEE Transactions on Neural Networks. 8(6). 1507–1517. 31 indexed citations

13.

Lawrence, Sandra, C. Lee Giles, Ah Chung Tsoi, & Andrew D. Back. (1997). Face recognition: a convolutional neural-network approach. IEEE Transactions on Neural Networks. 8(1). 98–113. 2060 indexed citations breakdown →

14.

Lawrence, Steve, Ah Chung Tsoi, & Andrew D. Back. (1995). The Gamma MLP for Speech Phoneme Recognition. Neural Information Processing Systems. 8. 785–791. 9 indexed citations

15.

Tsoi, Ah Chung & Andrew D. Back. (1995). Static and dynamic preprocessing methods in neural networks. Engineering Applications of Artificial Intelligence. 8(6). 633–642. 8 indexed citations

16.

Back, Andrew D. & Ah Chung Tsoi. (1994). A Comparison of Discrete-Time Operator Models for Nonlinear System Identification. Neural Information Processing Systems. 7. 883–890. 10 indexed citations

17.

Tsoi, Ah Chung & Andrew D. Back. (1994). Locally recurrent globally feedforward networks: a critical review of architectures. IEEE Transactions on Neural Networks. 5(2). 229–239. 195 indexed citations

18.

Back, Andrew D.. (1993). A simplified gradient algorithm for IIR synapse Multilayer Perceptron. Neural Networks. 5. 456–462. 10 indexed citations

19.

Back, Andrew D. & Ah Chung Tsoi. (1992). An Adaptive Lattice Architecture for Dynamic Multilayer Perceptrons. Neural Computation. 4(6). 922–931. 11 indexed citations

20.

Back, Andrew D. & Ah Chung Tsoi. (1992). Representational Capabilities of Multilayer Feedforward Networks with Time-Delay Synapses. 3064–3065. 2 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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