Simon Welker

653 total citations · 1 hit paper
21 papers, 322 citations indexed

About

Simon Welker is a scholar working on Signal Processing, Artificial Intelligence and Radiation. According to data from OpenAlex, Simon Welker has authored 21 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Signal Processing, 9 papers in Artificial Intelligence and 4 papers in Radiation. Recurrent topics in Simon Welker's work include Speech and Audio Processing (13 papers), Music and Audio Processing (8 papers) and Speech Recognition and Synthesis (8 papers). Simon Welker is often cited by papers focused on Speech and Audio Processing (13 papers), Music and Audio Processing (8 papers) and Speech Recognition and Synthesis (8 papers). Simon Welker collaborates with scholars based in Germany, Finland and Netherlands. Simon Welker's co-authors include Timo Gerkmann, Julius Richter, Jean-Marie Lemercier, Vesa Välimäki, Henry N. Chapman, Muhamed Amin, Alexander Richard, Jochen Küpper, Shinji Watanabe and Nale Lehmann‐Willenbrock and has published in prestigious journals such as IEEE Transactions on Image Processing, Computer Physics Communications and IEEE Signal Processing Magazine.

In The Last Decade

Simon Welker

20 papers receiving 295 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.

Speech Enhancement and Dereverberation With Diffusion-Based Generative Models

2023 118 citations Julius Richter, Simon Welker et al. IEEE/ACM Transactions on Audio Speech and Language Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Simon Welker Germany	8	255	193	57	34	17	21	322
Vishak Gopal United States	5	229 0.9×	240 1.2×	58 1.0×	34 1.0×	33 1.9×	11	351
Xiaojia Zhao United States	7	358 1.4×	287 1.5×	39 0.7×	34 1.0×	24 1.4×	8	395
Jean-Marie Lemercier Germany	6	191 0.7×	141 0.7×	41 0.7×	21 0.6×	15 0.9×	14	227
Daiki Takeuchi Japan	10	223 0.9×	136 0.7×	53 0.9×	39 1.1×	27 1.6×	29	306
Cheng Yu Taiwan	6	333 1.3×	232 1.2×	77 1.4×	34 1.0×	49 2.9×	12	372
Miquel Espi Japan	5	268 1.1×	158 0.8×	70 1.2×	28 0.8×	25 1.5×	13	295
Hemant A. Patil India	10	364 1.4×	299 1.5×	58 1.0×	46 1.4×	32 1.9×	21	398
Sherif Abdulatif Germany	9	106 0.4×	88 0.5×	33 0.6×	62 1.8×	15 0.9×	14	254
Chang Huai You Singapore	11	251 1.0×	214 1.1×	69 1.2×	48 1.4×	27 1.6×	30	323

Countries citing papers authored by Simon Welker

Since Specialization

Citations

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

Fields of papers citing papers by Simon Welker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simon Welker

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

All Works

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20 of 20 papers shown

1.

Lemercier, Jean-Marie, et al.. (2025). Unsupervised Blind Joint Dereverberation and Room Acoustics Estimation With Diffusion Models. IEEE Transactions on Audio Speech and Language Processing. 33. 2244–2258. 2 indexed citations

2.

Lemercier, Jean-Marie, et al.. (2024). Diffusion Models for Audio Restoration: A review. IEEE Signal Processing Magazine. 41(6). 72–84. 6 indexed citations

3.

Welker, Simon, et al.. (2024). Live Iterative Ptychography with Projection-Based Algorithms. 2455–2459. 1 indexed citations

4.

Welker, Simon, et al.. (2024). The PESQetarian: On the Relevance of Goodhart's Law for Speech Enhancement. 3854–3858. 3 indexed citations

5.

Lemercier, Jean-Marie, et al.. (2024). BUDDy: Single-Channel Blind Unsupervised Dereverberation with Diffusion Models. Aaltodoc (Aalto University). 120–124. 6 indexed citations

6.

Welker, Simon, et al.. (2024). A Flexible Online Framework for Projection-Based Stft Phase Retrieval. 10. 846–850. 1 indexed citations

7.

Welker, Simon, Henry N. Chapman, & Timo Gerkmann. (2024). DriftRec: Adapting Diffusion Models to Blind JPEG Restoration. IEEE Transactions on Image Processing. 33. 2795–2807. 6 indexed citations

8.

Welker, Simon, et al.. (2024). EMOCONV-Diff: Diffusion-Based Speech Emotion Conversion for Non-Parallel and in-the-Wild Data. 11651–11655. 2 indexed citations

9.

Richter, Julius, et al.. (2024). EARS: An Anechoic Fullband Speech Dataset Benchmarked for Speech Enhancement and Dereverberation. 4873–4877. 8 indexed citations

10.

Richter, Julius, et al.. (2023). Speech Enhancement and Dereverberation With Diffusion-Based Generative Models. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 2351–2364. 118 indexed citations breakdown →

11.

Welker, Simon, et al.. (2023). DiffPhase: Generative Diffusion-Based STFT Phase Retrieval. 1–5. 7 indexed citations

12.

Welker, Simon, et al.. (2023). Reducing the Prior Mismatch of Stochastic Differential Equations for Diffusion-based Speech Enhancement. 3809–3813. 14 indexed citations

13.

Lemercier, Jean-Marie, Julius Richter, Simon Welker, & Timo Gerkmann. (2023). StoRM: A Diffusion-Based Stochastic Regeneration Model for Speech Enhancement and Dereverberation. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 2724–2737. 54 indexed citations

14.

Lemercier, Jean-Marie, Julius Richter, Simon Welker, & Timo Gerkmann. (2023). Analysing Diffusion-based Generative Approaches Versus Discriminative Approaches for Speech Restoration. 1–5. 18 indexed citations

15.

Richter, Julius, et al.. (2023). Speech Signal Improvement Using Causal Generative Diffusion Models. 1–2. 4 indexed citations

16.

Lemercier, Jean-Marie, Simon Welker, & Timo Gerkmann. (2023). Diffusion Posterior Sampling for Informed Single-Channel Dereverberation. 1–5. 4 indexed citations

17.

Welker, Simon, Julius Richter, & Timo Gerkmann. (2022). Speech Enhancement with Score-Based Generative Models in the Complex STFT Domain. Interspeech 2022. 2928–2932. 54 indexed citations

18.

Welker, Simon, et al.. (2022). DEEP ITERATIVE PHASE RETRIEVAL FOR PTYCHOGRAPHY. DESY Publication Database (PUBDB) (Deutsches Elektronen-Synchrotron).

19.

Welker, Simon, et al.. (2022). Deep Iterative Phase Retrieval for Ptychography. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 1591–1595. 4 indexed citations

20.

Welker, Simon, Muhamed Amin, & Jochen Küpper. (2021). CMInject: Python framework for the numerical simulation of nanoparticle injection pipelines. Computer Physics Communications. 270. 108138–108138. 2 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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