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.
Advances in Variational Inference
2018349 citationsHedvig Kjellström, Stephan Mandt et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Hedvig Kjellström
Since
Specialization
Citations
This map shows the geographic impact of Hedvig Kjellström'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 Hedvig Kjellström with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hedvig Kjellström more than expected).
Fields of papers citing papers by Hedvig Kjellström
This network shows the impact of papers produced by Hedvig Kjellström. 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 Hedvig Kjellström. The network helps show where Hedvig Kjellström may publish in the future.
Co-authorship network of co-authors of Hedvig Kjellström
This figure shows the co-authorship network connecting the top 25 collaborators of Hedvig Kjellström.
A scholar is included among the top collaborators of Hedvig Kjellström 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 Hedvig Kjellström. Hedvig Kjellström is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zhang, Kun, et al.. (2019). Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation. KTH Publication Database DiVA (KTH Royal Institute of Technology). 32. 12773–12784.1 indexed citations
6.
Kucherenko, Taras, et al.. (2019). Should Beat Gestures Be Learned Or Designed? : A Benchmarking User Study. Ghent University Academic Bibliography (Ghent University).5 indexed citations
7.
Kucherenko, Taras & Hedvig Kjellström. (2018). A Neural Network Approach to Missing Marker Reconstruction.. arXiv (Cornell University).6 indexed citations
8.
Zhang, Cheng, Hedvig Kjellström, & Stephan Mandt. (2017). Balanced Mini-batch Sampling for SGD Using Determinantal Point Processes.. Uncertainty in Artificial Intelligence.2 indexed citations
Zhang, Cheng, Carl Henrik Ek, Andreas Damianou, & Hedvig Kjellström. (2013). Factorized topic models. KTH Publication Database DiVA (KTH Royal Institute of Technology).2 indexed citations
Pokorny, Florian T., Carl Henrik Ek, Hedvig Kjellström, & Danica Kragić. (2012). Topological constraints and kernel-based density estimation. Bristol Research (University of Bristol). 25.1 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.