Philip Bachman

18 papers and 1.4k indexed citations i.

About

Philip Bachman is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Philip Bachman has authored 18 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 2 papers in Molecular Biology. Recurrent topics in Philip Bachman’s work include Topic Modeling (5 papers), Multimodal Machine Learning Applications (4 papers) and Generative Adversarial Networks and Image Synthesis (4 papers). Philip Bachman is often cited by papers focused on Topic Modeling (5 papers), Multimodal Machine Learning Applications (4 papers) and Generative Adversarial Networks and Image Synthesis (4 papers). Philip Bachman collaborates with scholars based in Canada, United States and United Kingdom. Philip Bachman's co-authors include Doina Precup, Peter Henderson, Joëlle Pineau, Riashat Islam, David Meger, Alessandro Sordoni, Adam Trischler, Xingdi Yuan, Kaheer Suleman and Justin Harris and has published in prestigious journals such as Bioinformatics, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) and arXiv (Cornell University).

In The Last Decade

Co-authorship network of co-authors of Philip Bachman i

Fields of papers citing papers by Philip Bachman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Philip Bachman

Since Specialization
Citations

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

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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