Erich Elsen

9.2k citations
17 papers · 595 indexed · h-index 11

Erich Elsen

16 papers receiving 557 citations

Peers

Erich Elsen
Comparison fields: 5 of 70
  • Hardware and Architecture 182
  • Computer Graphics and Computer-Aided Design 36
  • Computer Vision and Pattern Recognition 169
  • Computational Mechanics 152
  • Computational Mathematics 4
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Citations per year

Countries citing papers authored by Erich Elsen

Since Specialization
Citations

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

Fields of papers citing papers by Erich Elsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

17 of 17 papers shown
#Work
1 20220
2
Practical Real Time Recurrent Learning with a Sparse Approximation
20213
3 20212
4
Rigging the Lottery: Making All Tickets Winners
202019
5 202011
6 201851
7
Mixed Precision Training
201762
8
Persistent RNNs: stashing recurrent weights on-chip
201636
9
DSD: Dense-Sparse-Dense Training for Deep Neural Networks
201612
10
VertexAPI2 – A Vertex-Program API for Large Graph Computations on the GPU
20147
11 2011144
12 20107
13 201010
14 20103
15 2008166
16 200833
17 200629

About Erich Elsen

Erich Elsen is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Artificial Intelligence and Signal Processing, having authored 17 papers that have together received 595 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (5 papers), Domain Adaptation and Few-Shot Learning (5 papers), Advancements in Photolithography Techniques (3 papers), Topic Modeling (2 papers), Distributed and Parallel Computing Systems (2 papers), Advanced Data Storage Technologies (2 papers), Music and Audio Processing (2 papers) and Parallel Computing and Optimization Techniques (2 papers). The work is most often cited by research in Hardware and Architecture (182 citations), Computer Graphics and Computer-Aided Design (36 citations), Computer Vision and Pattern Recognition (169 citations), Computational Mechanics (152 citations) and Computational Mathematics (4 citations). Erich Elsen has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Eric Darve, Patrick LeGresley, Pat Hanrahan, Zachary DeVito, Frank Ham, Montserrat Medina, N. Joubert, Francisco Palacios, Alex Aiken and S. P. Oakley. Their work appears in journals such as Journal of the Mechanics and Physics of Solids, Journal of Computational Physics, Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE, International Conference on Machine Learning and arXiv (Cornell University).

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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