Ivan Kobyzev

1.5k total citations · 1 hit paper
16 papers, 691 citations indexed

About

Ivan Kobyzev is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Mathematical Physics. According to data from OpenAlex, Ivan Kobyzev has authored 16 papers receiving a total of 691 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 2 papers in Mathematical Physics. Recurrent topics in Ivan Kobyzev's work include Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Ivan Kobyzev is often cited by papers focused on Topic Modeling (7 papers), Natural Language Processing Techniques (5 papers) and Domain Adaptation and Few-Shot Learning (4 papers). Ivan Kobyzev collaborates with scholars based in Canada, Sweden and Austria. Ivan Kobyzev's co-authors include Marcus A. Brubaker, Simon J. D. Prince, Mehdi Rezagholizadeh, Ali Ghodsi, Simon Prince, Yaoliang Yu, Priyank Jaini, Pascal Poupart, Peter Forsyth and Peng Lu and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences and Journal of Mathematical Sciences.

In The Last Decade

Ivan Kobyzev

12 papers receiving 665 citations

Hit Papers

align trajectories

What are hit papers?

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.

Normalizing Flows: An Introduction and Review of Current Methods

2020 616 citations Ivan Kobyzev, Simon J. D. Prince et al. IEEE Transactions on Pattern Analysis and Machine Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Ivan Kobyzev Canada	5	277	187	80	77	48	16	691
Yiming Chen China	13	385 1.4×	141 0.8×	55 0.7×	61 0.8×	41 0.9×	73	748
Lin F. Yang United States	14	280 1.0×	83 0.4×	38 0.5×	34 0.4×	54 1.1×	98	705
Marcelo Pereyra United Kingdom	18	286 1.0×	201 1.1×	37 0.5×	65 0.8×	12 0.3×	53	930
Dan Kalman United States	13	140 0.5×	181 1.0×	265 3.3×	61 0.8×	53 1.1×	66	1.1k
Robert Azencott United States	17	132 0.5×	214 1.1×	25 0.3×	29 0.4×	31 0.6×	76	1.1k
Marcelo P. de Albuquerque Brazil	11	147 0.5×	332 1.8×	60 0.8×	26 0.3×	8 0.2×	33	834
Joseph J. K. Ó Ruanaidh Switzerland	8	186 0.7×	984 5.3×	25 0.3×	193 2.5×	40 0.8×	9	1.4k
Alfredo Buttari France	19	100 0.4×	53 0.3×	49 0.6×	47 0.6×	28 0.6×	42	1.4k
J. Barhen United States	18	487 1.8×	140 0.7×	142 1.8×	42 0.5×	185 3.9×	105	1.3k
Michel Daoud Yacoub Brazil	30	202 0.7×	64 0.3×	14 0.2×	104 1.4×	21 0.4×	218	4.2k

Countries citing papers authored by Ivan Kobyzev

Since Specialization

Citations

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

Fields of papers citing papers by Ivan Kobyzev

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ivan Kobyzev

This figure shows the co-authorship network connecting the top 25 collaborators of Ivan Kobyzev. A scholar is included among the top collaborators of Ivan Kobyzev 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 Ivan Kobyzev. Ivan Kobyzev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

1.

Huang, Chenyang, et al.. (2024). OTTAWA: Optimal TransporT Adaptive Word Aligner for Hallucination and Omission Translation Errors Detection. 6322–6334.

2.

Kobyzev, Ivan, et al.. (2024). Resonance RoPE: Improving Context Length Generalization of Large Language Models. 586–598.

3.

Rezagholizadeh, Mehdi, et al.. (2023). DyLoRA: Parameter-Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation. 3274–3287. 37 indexed citations

4.

Liu, Runcheng, et al.. (2023). Attribute Controlled Dialogue Prompting. 2380–2389. 1 indexed citations

5.

Kobyzev, Ivan, Mehdi Rezagholizadeh, Tianda Li, et al.. (2023). Do we need Label Regularization to Fine-tune Pre-trained Language Models?. 166–177.

6.

Lu, Peng, et al.. (2023). Efficient Classification of Long Documents via State-Space Models. 6559–6565. 1 indexed citations

7.

Lu, Peng, et al.. (2022). Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging. 4948–4954. 4 indexed citations

8.

Kobyzev, Ivan, et al.. (2022). Continuation KD: Improved Knowledge Distillation through the Lens of Continuation Optimization. 5260–5269. 2 indexed citations

9.

Jaini, Priyank, Ivan Kobyzev, Yaoliang Yu, & Marcus A. Brubaker. (2020). Tails of Lipschitz Triangular Flows. International Conference on Machine Learning. 1. 4673–4681. 8 indexed citations

10.

Kobyzev, Ivan, Simon J. D. Prince, & Marcus A. Brubaker. (2020). Normalizing Flows: An Introduction and Review of Current Methods. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(11). 3964–3979. 616 indexed citations breakdown →

11.

Kazemi, Seyed Mehran, et al.. (2019). Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey.. arXiv (Cornell University). 10 indexed citations

12.

Kobyzev, Ivan, Simon Prince, & Marcus A. Brubaker. (2019). Normalizing Flows: Introduction and Ideas.. arXiv (Cornell University). 8 indexed citations

13.

Serb, Alexander, et al.. (2019). A semi-holographic hyperdimensional representation system for hardware-friendly cognitive computing. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 378(2164). 20190162–20190162. 1 indexed citations

14.

Jaini, Priyank, Ivan Kobyzev, Marcus A. Brubaker, & Yaoliang Yu. (2019). Tails of Triangular Flows.. 2 indexed citations

15.

Kobyzev, Ivan, et al.. (2018). Anti-Yetter-Drinfeld Modules for Quasi-Hopf Algebras. Symmetry Integrability and Geometry Methods and Applications. 1 indexed citations

16.

Kobyzev, Ivan. (2013). An algebraic analog of the borel construction and its properties. Journal of Mathematical Sciences. 188(5). 621–639.

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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