Jesse Engel

26 papers receiving 809 citations

Peers

Jesse Engel
Comparison fields: 5 of 67
  • Signal Processing 146
  • Materials Chemistry 426
  • Electrical and Electronic Engineering 494
  • Computer Vision and Pattern Recognition 161
  • Electronic, Optical and Magnetic Materials 100
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Woobin Lee United States
Hung‐Yu Chen Taiwan
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Citations per year

Countries citing papers authored by Jesse Engel

Since Specialization
Citations

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

Fields of papers citing papers by Jesse Engel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jesse Engel, 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 Jesse Engel Line = papers co-authored together Jesse Engel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011208
2 2013139
3 2014128
4
Persistent RNNs: stashing recurrent weights on-chip
201643
5 201241
6 201639
7 201333
8 201333
9
A Hierarchical Latent Vector Model for Learning Long-Term Structure in Music
201829
10
Hierarchical Variational Autoencoders for Music
201725
11 202223
12 201916
13 201916
14
MidiMe: Personalizing a MusicVAE model with user data
201914
15 201813
16
End to end speech recognition in English and Mandarin
201610
17
Self-supervised Pitch Detection by Inverse Audio Synthesis
20208
18 20207
19
Learning Latent Representations of Music to Generate Interactive Musical Palettes
20186
20
Tone Transfer: In-Browser Interactive Neural Audio Synthesis.
20215

About Jesse Engel

Jesse Engel is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Artificial Intelligence, Materials Chemistry and Electrical and Electronic Engineering, having authored 26 papers that have together received 856 indexed citations. Recurring topics across this work include Music and Audio Processing (16 papers), Music Technology and Sound Studies (10 papers), Speech and Audio Processing (6 papers), Quantum Dots Synthesis And Properties (5 papers), Speech Recognition and Synthesis (5 papers), Chalcogenide Semiconductor Thin Films (4 papers), Advanced Memory and Neural Computing (4 papers) and Phase-change materials and chalcogenides (3 papers). The work is most often cited by research in Signal Processing (146 citations), Materials Chemistry (426 citations), Electrical and Electronic Engineering (494 citations), Computer Vision and Pattern Recognition (161 citations) and Electronic, Optical and Magnetic Materials (100 citations). Jesse Engel has collaborated with scholars based in United States, Taiwan and Germany. Frequent co-authors include A. Paul Alivisatos, Vivian E. Ferry, Wanli Ma, Sarah L. Swisher, Harry A. Atwater, Trevor D. Ewers, Adam Paul Roberts, H.‐S. Philip Wong, Sarah White and Karthish Manthiram. Their work appears in journals such as ACS Nano, Angewandte Chemie International Edition, Scientific Reports, Chemistry of Materials and Journal of the American Chemical Society.

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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