Countries citing papers authored by Christopher De
Since
Specialization
Citations
This map shows the geographic impact of Christopher De'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 Christopher De with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher De more than expected).
This network shows the impact of papers produced by Christopher De. 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 Christopher De. The network helps show where Christopher De may publish in the future.
Co-authorship network of co-authors of Christopher De
This figure shows the co-authorship network connecting the top 25 collaborators of Christopher De.
A scholar is included among the top collaborators of Christopher De 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 Christopher De. Christopher De is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Lu, Yucheng & Christopher De. (2021). Optimal Complexity in Decentralized Training. International Conference on Machine Learning. 7111–7123.3 indexed citations
2.
Björck, Johan, Xiangyu Chen, Christopher De, Carla P. Gomes, & Kilian Q. Weinberger. (2021). Low-Precision Reinforcement Learning: Running Soft Actor-Critic in Half Precision. International Conference on Machine Learning. 980–991.4 indexed citations
Lu, Yucheng & Christopher De. (2020). Moniqua: Modulo Quantized Communication in Decentralized SGD. International Conference on Machine Learning. 1. 6415–6425.12 indexed citations
Zhao, Ritchie, et al.. (2019). Improving Neural Network Quantization using Outlier Channel Splitting. arXiv (Cornell University).2 indexed citations
7.
Yu, Tao & Christopher De. (2019). Numerically Accurate Hyperbolic Embeddings Using Tiling-Based Models. Neural Information Processing Systems. 32. 2021–2031.3 indexed citations
8.
De, Christopher, Ihab F. Ilyas, Benny Kimelfeld, Christopher Ré, & Theodoros Rekatsinas. (2019). A Formal Framework for Probabilistic Unclean Databases.. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 18.9 indexed citations
9.
Hua, Weizhe, Yuan Zhou, Christopher De, Zhiru Zhang, & G. Edward Suh. (2019). Channel Gating Neural Networks. Neural Information Processing Systems. 32. 1884–1894.25 indexed citations
10.
De, Christopher, et al.. (2019). Dimension-Free Bounds for Low-Precision Training. Neural Information Processing Systems. 32. 11728–11738.3 indexed citations
11.
Zhao, Ritchie, et al.. (2019). Improving Neural Network Quantization without Retraining using Outlier Channel Splitting. International Conference on Machine Learning. 7543–7552.32 indexed citations
Xu, Peng, Bryan He, Christopher De, Ioannis Mitliagkas, & Christopher Ré. (2018). Accelerated Stochastic Power Iteration. International Conference on Artificial Intelligence and Statistics. 58–67.10 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.