Jan Chorowski

5.7k total citations · 1 hit paper
18 papers, 886 citations indexed

About

Jan Chorowski is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jan Chorowski has authored 18 papers receiving a total of 886 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 6 papers in Signal Processing and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jan Chorowski's work include Speech Recognition and Synthesis (8 papers), Topic Modeling (6 papers) and Natural Language Processing Techniques (5 papers). Jan Chorowski is often cited by papers focused on Speech Recognition and Synthesis (8 papers), Topic Modeling (6 papers) and Natural Language Processing Techniques (5 papers). Jan Chorowski collaborates with scholars based in United States, Poland and United Kingdom. Jan Chorowski's co-authors include Jacek M. Żurada, Navdeep Jaitly, Jian Wang, Geoffrey E. Hinton, Gabriel Pereyra, Łukasz Kaiser, George Tucker, Yonghui Wu, Zhifeng Chen and Ron J. Weiss and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing and IEEE Transactions on Neural Networks.

In The Last Decade

Jan Chorowski

17 papers receiving 827 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.

Regularizing Neural Networks by Penalizing Confident Output Distributions

2017 178 citations Gabriel Pereyra, George Tucker et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jan Chorowski United States	10	648	209	176	49	36	18	886
Edmondo Trentin Italy	12	461 0.7×	175 0.8×	190 1.1×	67 1.4×	54 1.5×	52	744
Zi-Rui Wang China	11	374 0.6×	294 1.4×	71 0.4×	29 0.6×	32 0.9×	23	661
Boonserm Kijsirikul Thailand	16	376 0.6×	258 1.2×	74 0.4×	42 0.9×	49 1.4×	85	764
Jonas Gehring Germany	7	958 1.5×	450 2.2×	223 1.3×	34 0.7×	57 1.6×	13	1.2k
Jianpeng Cheng United Kingdom	9	612 0.9×	247 1.2×	64 0.4×	46 0.9×	22 0.6×	15	881
Lin Wei China	13	291 0.4×	169 0.8×	105 0.6×	80 1.6×	21 0.6×	62	739
Chao-Kai Chiang United States	4	325 0.5×	190 0.9×	49 0.3×	47 1.0×	21 0.6×	6	564
Dara Bahri United States	9	344 0.5×	207 1.0×	63 0.4×	49 1.0×	29 0.8×	15	629
Madhusudana Shashanka United States	17	291 0.4×	182 0.9×	414 2.4×	47 1.0×	34 0.9×	28	757

Countries citing papers authored by Jan Chorowski

Since Specialization

Citations

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

Fields of papers citing papers by Jan Chorowski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Chorowski

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

All Works

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18 of 18 papers shown

Chorowski, Jan, et al.. (2023). Efficient Transformers with Dynamic Token Pooling. 6403–6417. 9 indexed citations

Chorowski, Jan, et al.. (2022). Contrastive Prediction Strategies for Unsupervised Segmentation and Categorization of Phonemes and Words. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 3189–3193. 13 indexed citations

Chorowski, Jan, et al.. (2021). Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw. arXiv (Cornell University). 6 indexed citations

Łańcucki, Adrian, Jan Chorowski, Ricard Marxer, et al.. (2020). Robust Training of Vector Quantized Bottleneck Models. 1–7. 14 indexed citations

Khurana, Sameer, Antoine Laurent, Wei-Ning Hsu, et al.. (2020). A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning. arXiv (Cornell University). 3790–3794. 14 indexed citations

Łańcucki, Adrian, et al.. (2019). Lattice Generation in Attention-Based Speech Recognition Models. 2225–2229. 9 indexed citations

Foerster, Jakob, Justin Gilmer, Jascha Sohl‐Dickstein, Jan Chorowski, & David Sussillo. (2017). Input Switched Affine Networks: An RNN Architecture Designed for Interpretability. International Conference on Machine Learning. 1136–1145. 6 indexed citations

Chorowski, Jan & Navdeep Jaitly. (2017). Towards Better Decoding and Language Model Integration in Sequence to Sequence Models. 523–527. 178 indexed citations

Weiss, Ron J., Jan Chorowski, Navdeep Jaitly, Yonghui Wu, & Zhifeng Chen. (2017). Sequence-to-Sequence Models Can Directly Translate Foreign Speech. 2625–2629. 155 indexed citations

10.

Pereyra, Gabriel, George Tucker, Jan Chorowski, Łukasz Kaiser, & Geoffrey E. Hinton. (2017). Regularizing Neural Networks by Penalizing Confident Output Distributions. arXiv (Cornell University). 178 indexed citations breakdown →

11.

Bahdanau, Dzmitry, Philémon Brakel, Nan Rosemary Ke, et al.. (2016). Task Loss Estimation for Structured Prediction. 1 indexed citations

12.

Merriënboer, Bart van, Dmitry Bogdanov, Jan Chorowski, et al.. (2015). Blocks and Fuel. Zenodo (CERN European Organization for Nuclear Research). 3 indexed citations

13.

Chorowski, Jan & Jacek M. Żurada. (2014). Learning Understandable Neural Networks With Nonnegative Weight Constraints. IEEE Transactions on Neural Networks and Learning Systems. 26(1). 62–69. 99 indexed citations

14.

Żurada, Jacek M., et al.. (2013). Nonnegative Matrix Factorization and its application to pattern analysis and text mining. Federated Conference on Computer Science and Information Systems. 11–16. 1 indexed citations

15.

Chorowski, Jan, Jian Wang, & Jacek M. Żurada. (2013). Review and performance comparison of SVM- and ELM-based classifiers. Neurocomputing. 128. 507–516. 161 indexed citations

16.

Chorowski, Jan & Jacek M. Żurada. (2012). Obtaining Full Regularization Paths for Robust Sparse Coding with Applications to Face Recognition. 69. 356–361. 1 indexed citations

17.

Ensarı, Tolga, Jan Chorowski, & Jacek M. Żurada. (2012). Occluded Face Recognition Using Correntropy-Based Nonnegative Matrix Factorization. 5. 606–609. 3 indexed citations

18.

Chorowski, Jan & Jacek M. Żurada. (2011). Extracting Rules From Neural Networks as Decision Diagrams. IEEE Transactions on Neural Networks. 22(12). 2435–2446. 35 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.

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