Bill Baird

807 citations
29 papers · 571 · h-index 10

Impact in

Papers in

Bill Baird

28 papers receiving 535 citations

Peers

Bill Baird
Comparison fields: 5 of 88
  • Cognitive Neuroscience 382
  • Sensory Systems 80
  • Statistical and Nonlinear Physics 85
  • Cellular and Molecular Neuroscience 100
  • Artificial Intelligence 160
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Citations per year

Countries citing papers authored by Bill Baird

Since Specialization
Citations

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

Fields of papers citing papers by Bill Baird

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Bill Baird, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bill Baird Line = papers co-authored together Bill Baird links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1987134
2 1986122
3 1987112
4 200443
5 200423
6 199022
7 200718
8 199315
9 199511
10
A normal form projection algorithm for associative memory
199310
11
Effects of applied electric current fields on cortical neural activity
19937
12
Associative Memory in a Simple Model of Oscillating Cortex
19897
13
A Bifurcation Theory Approach to the Programming of Periodic Attractors in Network Models of Olfactory Cortex
19887
14 19907
15 20066
16 19914
17 20134
18 19993
19
Bifurcation analysis of oscillating network model of pattern recognition in the rabbit olfactory bulb
19873
20
Synchronization and Grammatical Inference in an Oscillating Elman Net
19922

About Bill Baird

Bill Baird is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Cellular and Molecular Neuroscience, Sensory Systems and Computer Networks and Communications, having authored 29 papers that have together received 571 indexed citations. Recurring topics across this work include Neural dynamics and brain function (13 papers), Neural Networks and Applications (11 papers), Olfactory and Sensory Function Studies (4 papers), Advanced Memory and Neural Computing (2 papers), Diverse Educational Innovations Studies (2 papers), Neuroscience and Music Perception (2 papers), Nonlinear Dynamics and Pattern Formation (2 papers) and Neurobiology and Insect Physiology Research (2 papers). The work is most often cited by research in Cognitive Neuroscience (382 citations), Sensory Systems (80 citations), Statistical and Nonlinear Physics (85 citations), Cellular and Molecular Neuroscience (100 citations) and Artificial Intelligence (160 citations). Bill Baird has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Walter Freeman, Walter J. Freeman, Frank H. Eeckman, Morris W. Hirsch, Marram P. Olson, Michael Trumpis, Linda Larson‐Prior, Don L. Jewett, Gideon P. Caplovitz and Laura Rees. Their work appears in journals such as Behavioral Neuroscience, Physica D Nonlinear Phenomena, Neurocomputing, Journal of Clinical and Experimental Neuropsychology and Biosystems.

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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