William T. Adler

609 total citations
6 papers, 208 citations indexed

About

William T. Adler is a scholar working on Statistics and Probability, Cognitive Neuroscience and Genetics. According to data from OpenAlex, William T. Adler has authored 6 papers receiving a total of 208 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Statistics and Probability, 2 papers in Cognitive Neuroscience and 2 papers in Genetics. Recurrent topics in William T. Adler's work include Statistical Methods and Bayesian Inference (2 papers), Neural dynamics and brain function (2 papers) and Reading and Literacy Development (2 papers). William T. Adler is often cited by papers focused on Statistical Methods and Bayesian Inference (2 papers), Neural dynamics and brain function (2 papers) and Reading and Literacy Development (2 papers). William T. Adler collaborates with scholars based in United States. William T. Adler's co-authors include Wei Ji, Marisa Carrasco, Rachel N. Denison, Glenn D. Rosen, Albert M. Galaburda, Maryann P. Platt, Samuel S.‐H. Wang, Timothy A. Currier and Mary Miu Yee Waye and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Neuroscience.

In The Last Decade

William T. Adler

6 papers receiving 208 citations

Peers

William T. Adler

CN

DEP

ECP

GENET

GDS

Doris Pischedda Germany

Simon D. Lilburn Australia

John L. Jones United States

Alexis Barbot France

Habiba Azab United States

Vy A. Vo United States

Shiva Farashahi United States

Ting Qi China

Nietzsche H. L. Lam Netherlands

J. D. Cohen United States

Doris Pischedda Germany

William T. Adler

94 ×0.6

CN

31 ×0.8

DEP

27 ×0.9

ECP

4 ×0.2

GENET

6 ×0.3

GDS

Citations per year, relative to William T. Adler William T. Adler (= 1×) peers Doris Pischedda

Countries citing papers authored by William T. Adler

Since Specialization

Citations

This map shows the geographic impact of William T. Adler'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 William T. Adler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William T. Adler more than expected).

Fields of papers citing papers by William T. Adler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William T. Adler. 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 William T. Adler. The network helps show where William T. Adler may publish in the future.

Co-authorship network of co-authors of William T. Adler

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

All Works

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6 of 6 papers shown

1.

Adler, William T. & Wei Ji. (2018). Limitations of Proposed Signatures of Bayesian Confidence. Neural Computation. 30(12). 3327–3354. 27 indexed citations

2.

Denison, Rachel N., William T. Adler, Marisa Carrasco, & Wei Ji. (2018). Humans incorporate attention-dependent uncertainty into perceptual decisions and confidence. Proceedings of the National Academy of Sciences. 115(43). 11090–11095. 68 indexed citations

3.

Adler, William T. & Wei Ji. (2018). Comparing Bayesian and non-Bayesian accounts of human confidence reports. PLoS Computational Biology. 14(11). e1006572–e1006572. 60 indexed citations

4.

Adler, William T. & Samuel S.‐H. Wang. (2018). Response to Cho and Liu, “Sampling from complicated and unknown distributions: Monte Carlo and Markov chain Monte Carlo methods for redistricting”. Physica A Statistical Mechanics and its Applications. 516. 591–593. 5 indexed citations

5.

Adler, William T., et al.. (2013). Position of Neocortical Neurons Transfected at Different Gestational Ages with shRNA Targeted against Candidate Dyslexia Susceptibility Genes. PLoS ONE. 8(5). e65179–e65179. 22 indexed citations

6.

Platt, Maryann P., et al.. (2013). Embryonic disruption of the candidate dyslexia susceptibility gene homolog Kiaa0319-like results in neuronal migration disorders. Neuroscience. 248. 585–593. 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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