Maitreya Patel

489 total citations
17 papers, 133 citations indexed

About

Maitreya Patel is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Maitreya Patel has authored 17 papers receiving a total of 133 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 9 papers in Signal Processing and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Maitreya Patel's work include Speech Recognition and Synthesis (11 papers), Speech and Audio Processing (7 papers) and Music and Audio Processing (7 papers). Maitreya Patel is often cited by papers focused on Speech Recognition and Synthesis (11 papers), Speech and Audio Processing (7 papers) and Music and Audio Processing (7 papers). Maitreya Patel collaborates with scholars based in India, United States and Brazil. Maitreya Patel's co-authors include Hemant A. Patil, Mirali Purohit, Nirmesh J. Shah, Rodrigo Capobianco Guido, Cheng Sheng, Chitta Baral, Kyle Min, Tejas Gokhale, Hemant A. Patil and Changhoon Kim and has published in prestigious journals such as Neural Networks, Maryland Shared Open Access Repository (USMAI Consortium) and Proceedings of the AAAI Conference on Artificial Intelligence.

In The Last Decade

Maitreya Patel

15 papers receiving 131 citations

Peers

Maitreya Patel

AI

SP

PHYSI

CVPR

ECP

Mirali Purohit United States

Erfan Loweimi United Kingdom

Ryo Aihara Japan

Nirmesh J. Shah India

Xurong Xie China

Nagaraj Adiga India

Jean-François Sérignat United States

Danwei Cai China

Hemant Kumar Kathania India

Ville Vestman Finland

Mirali Purohit United States

Maitreya Patel

58 ×0.6

AI

34 ×0.4

SP

43 ×0.9

PHYSI

8 ×0.3

CVPR

15 ×0.8

ECP

Citations per year, relative to Maitreya Patel Maitreya Patel (= 1×) peers Mirali Purohit

Countries citing papers authored by Maitreya Patel

Since Specialization

Citations

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

Fields of papers citing papers by Maitreya Patel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maitreya Patel

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

All Works

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17 of 17 papers shown

1.

Patel, Maitreya, Tejas Gokhale, Chitta Baral, & Yezhou Yang. (2024). ConceptBed: Evaluating Concept Learning Abilities of Text-to-Image Diffusion Models. Proceedings of the AAAI Conference on Artificial Intelligence. 38(13). 14554–14562. 3 indexed citations

2.

Kim, Changhoon, et al.. (2024). WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models. 8974–8983. 10 indexed citations

3.

Patel, Maitreya, et al.. (2024). ECLIPSE: A Resource-Efficient Text-to-Image Prior for Image Generations. 9069–9078.

4.

Baral, Chitta, et al.. (2024). TripletCLIP: Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives. 32731–32760.

5.

Patel, Maitreya, et al.. (2023). Attentions for Short Duration Speech Classification. 1340–1344. 1 indexed citations

6.

Patel, Maitreya, et al.. (2022). CRIPP-VQA: Counterfactual Reasoning about Implicit Physical Properties via Video Question Answering. Maryland Shared Open Access Repository (USMAI Consortium). 9856–9870. 4 indexed citations

7.

Purohit, Mirali, et al.. (2021). Residual Neural Network precisely quantifies dysarthria severity-level based on short-duration speech segments. Neural Networks. 139. 105–117. 42 indexed citations

8.

Patel, Maitreya, et al.. (2020). CinC-GAN for Effective F₀prediction for Whisper-to-Normal Speech Conversion. 411–415. 4 indexed citations

9.

Patel, Maitreya, et al.. (2020). Mspec-Net : Multi-Domain Speech Conversion Network. 7764–7768. 9 indexed citations

10.

Patel, Maitreya, et al.. (2020). Effectiveness of Transfer Learning on Singing Voice Conversion in the Presence of Background Music. 10. 1–5. 6 indexed citations

11.

Purohit, Mirali, et al.. (2020). Weak Speech Supervision: A case study of Dysarthria Severity Classification. abs 1506 1195. 101–105. 4 indexed citations

12.

Purohit, Mirali, et al.. (2020). Intelligibility Improvement of Dysarthric Speech using MMSE DiscoGAN. 1–5. 8 indexed citations

13.

Patel, Maitreya, et al.. (2019). Novel Adaptive Generative Adversarial Network for Voice Conversion. 1273–1281. 11 indexed citations

14.

Shah, Nirmesh J., et al.. (2019). Effectiveness of Cross-Domain Architectures for Whisper-to-Normal Speech Conversion. 1–5. 16 indexed citations

15.

Patel, Maitreya, et al.. (2019). Novel Inception-GAN for Whispered-to-Normal Speech Conversion. 87–92. 8 indexed citations

16.

Patel, Maitreya, et al.. (2019). PolSAR Band-to-Band Image Translation Using Conditional Adversarial Networks. 1–4. 3 indexed citations

17.

Patel, Maitreya, et al.. (2019). AdaGAN: Adaptive GAN for Many-to-Many Non-Parallel Voice Conversion. 4 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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