Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Image Super-Resolution Via Iterative Refinement
20221.0k citationsChitwan Saharia, Jonathan Ho et al.IEEE Transactions on Pattern Analysis and Machine Intelligenceprofile →
Motion planning with sequential convex optimization and convex collision checking
2014539 citationsJohn Schulman, Yan Duan et al.The International Journal of Robotics Researchprofile →
On Distillation of Guided Diffusion Models
2023117 citationsChenlin Meng, Robin Rombach et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Jonathan Ho'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 Jonathan Ho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Ho more than expected).
This network shows the impact of papers produced by Jonathan Ho. 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 Jonathan Ho. The network helps show where Jonathan Ho may publish in the future.
Co-authorship network of co-authors of Jonathan Ho
This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Ho.
A scholar is included among the top collaborators of Jonathan Ho 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 Jonathan Ho. Jonathan Ho is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Meng, Chenlin, Robin Rombach, Ruiqi Gao, et al.. (2023). On Distillation of Guided Diffusion Models. 14297–14306.117 indexed citations breakdown →
5.
Saharia, Chitwan, Jonathan Ho, William Chan, et al.. (2022). Image Super-Resolution Via Iterative Refinement. IEEE Transactions on Pattern Analysis and Machine Intelligence. 45(4). 1–14.1022 indexed citations breakdown →
Theis, Lucas & Jonathan Ho. (2021). Importance weighted compression. International Conference on Learning Representations.1 indexed citations
8.
Kingma, Diederik P., Tim Salimans, Ben Poole, & Jonathan Ho. (2021). On Density Estimation with Diffusion Models. Neural Information Processing Systems. 34.1 indexed citations
Abbeel, Pieter, et al.. (2019). Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables. International Conference on Machine Learning. 3408–3417.7 indexed citations
13.
Ho, Jonathan, et al.. (2019). Compression with Flows via Local Bits-Back Coding. Neural Information Processing Systems. 32. 3874–3883.1 indexed citations
14.
Houthooft, Rein, Richard Y. Chen, Phillip Isola, et al.. (2018). Evolved Policy Gradients. arXiv (Cornell University). 31. 5400–5409.16 indexed citations
15.
Schulman, John, Yan Duan, Jonathan Ho, et al.. (2014). Motion planning with sequential convex optimization and convex collision checking. The International Journal of Robotics Research. 33(9). 1251–1270.539 indexed citations breakdown →
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.