Jared Sylvester

815 total citations
14 papers, 323 citations indexed

About

Jared Sylvester is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Safety Research. According to data from OpenAlex, Jared Sylvester has authored 14 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Artificial Intelligence, 5 papers in Cognitive Neuroscience and 2 papers in Safety Research. Recurrent topics in Jared Sylvester's work include Neural dynamics and brain function (5 papers), Neural Networks and Applications (4 papers) and Neural Networks and Reservoir Computing (3 papers). Jared Sylvester is often cited by papers focused on Neural dynamics and brain function (5 papers), Neural Networks and Applications (4 papers) and Neural Networks and Reservoir Computing (3 papers). Jared Sylvester collaborates with scholars based in United States and United Kingdom. Jared Sylvester's co-authors include Edward Raff, Mark McLean, James A. Reggia, Richard Zak, Nitesh V. Chawla, Charles Nicholas, Steven Mills, William Rand, Michelle Girvan and Michael F. Bunting and has published in prestigious journals such as Neural Computation, Neural Networks and Journal of Computer Virology and Hacking Techniques.

In The Last Decade

Jared Sylvester

14 papers receiving 305 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jared Sylvester United States	9	203	124	103	60	45	14	323
Raymond Hu United Kingdom	12	300 1.5×	82 0.7×	123 1.2×	41 0.7×	35 0.8×	20	480
Wenjie Wang China	14	125 0.6×	67 0.5×	356 3.5×	85 1.4×	20 0.4×	39	481
Weidong Chen China	11	366 1.8×	79 0.6×	136 1.3×	68 1.1×	31 0.7×	41	519
Licia Sbattella Italy	9	155 0.8×	104 0.8×	159 1.5×	77 1.3×	36 0.8×	42	297
Richard Harang United States	10	159 0.8×	145 1.2×	122 1.2×	170 2.8×	7 0.2×	30	340
A. Theodore Markettos United Kingdom	11	194 1.0×	82 0.7×	100 1.0×	35 0.6×	40 0.9×	25	340
Dayeol Lee United States	6	241 1.2×	87 0.7×	142 1.4×	129 2.1×	16 0.4×	8	412
Artur Janicki Poland	11	313 1.5×	258 2.1×	137 1.3×	63 1.1×	9 0.2×	49	482
Da Li United States	7	142 0.7×	23 0.2×	56 0.5×	72 1.2×	18 0.4×	17	280
Yuanlin Zhang United States	12	363 1.8×	86 0.7×	149 1.4×	50 0.8×	11 0.2×	39	523

Countries citing papers authored by Jared Sylvester

Since Specialization

Citations

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

Fields of papers citing papers by Jared Sylvester

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jared Sylvester. 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 Jared Sylvester. The network helps show where Jared Sylvester may publish in the future.

Co-authorship network of co-authors of Jared Sylvester

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

All Works

Sort: Min cites: Since: Top N: Style:

14 of 14 papers shown

1.

Raff, Edward, et al.. (2019). Barrage of Random Transforms for Adversarially Robust Defense. 6521–6530. 74 indexed citations

2.

Raff, Edward & Jared Sylvester. (2018). Gradient Reversal against Discrimination: A Fair Neural Network Learning Approach. 189–198. 14 indexed citations

3.

Raff, Edward & Jared Sylvester. (2018). Linear Models with Many Cores and CPUs: A Stochastic Atomic Update Scheme. 65–73. 2 indexed citations

4.

Raff, Edward, Jared Sylvester, & Steven Mills. (2018). Fair Forests. 243–250. 25 indexed citations

5.

Sylvester, Jared & James A. Reggia. (2016). Engineering neural systems for high-level problem solving. Neural Networks. 79. 37–52. 17 indexed citations

6.

Raff, Edward, et al.. (2016). An investigation of byte n-gram features for malware classification. Journal of Computer Virology and Hacking Techniques. 14(1). 1–20. 116 indexed citations

7.

Reggia, James A., et al.. (2014). The Computational Explanatory Gap. 12 indexed citations

8.

Sylvester, Jared, et al.. (2014). Space, Time, and Hurricanes: Investigating the Spatiotemporal Relationship Among Social Media Use, Donations, and Disasters. SSRN Electronic Journal. 2 indexed citations

9.

Sylvester, Jared, et al.. (2013). Controlling working memory with learned instructions. Neural Networks. 41. 23–38. 17 indexed citations

10.

Sylvester, Jared, et al.. (2013). Predictability of User Behavior in Social Media: Bottom-Up v. Top-Down Modeling. 102–107. 11 indexed citations

11.

Sylvester, Jared, et al.. (2013). Predictability of User Behavior in Social Media: Bottom-Up v Top-Down Modeling. SSRN Electronic Journal. 1 indexed citations

12.

Reggia, James A., et al.. (2009). A Simple Oscillatory Short-Term Memory.. 2 indexed citations

13.

Sylvester, Jared & James A. Reggia. (2009). Plasticity-Induced Symmetry Relationships Between Adjacent Self-Organizing Topographic Maps. Neural Computation. 21(12). 3429–3443. 4 indexed citations

14.

Sylvester, Jared & Nitesh V. Chawla. (2006). Evolutionary Ensemble Creation and Thinning. The 2006 IEEE International Joint Conference on Neural Network Proceedings. 4. 5148–5155. 26 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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