Sumit Chopra

20.1k citations
48 papers · 8.4k indexed · 6 hit papers · h-index 20

Impact in

Papers in

Sumit Chopra

41 papers receiving 8.0k citations

Hit Papers

Sequence Level Training with Recurrent Neural Networks 2016 · 308 citations
308200520262012201950010001.5k2.0k2.5k

Peers

Sumit Chopra
Comparison fields: 5 of 185
  • Health Informatics 301
  • Computer Vision and Pattern Recognition 4.2k
  • Artificial Intelligence 4.3k
  • Signal Processing 769
  • Media Technology 480
Replace Mehdi Mirza with:
Mehdi Mirza Canada
Sherjil Ozair United States
Jean Pouget-Abadie United States
Xiaofeng Zhu China
Àgata Lapedriza Spain
Raia Hadsell United States
Prayag Tiwari China
Gwanggil Jeon South Korea
Kyunghyun Cho United States
Sumit Chopra relative to Mehdi Mirza Canada Mehdi Mirza's profile →
Citations per field
00.5×9.1×
Mehdi Mirza · 1×
Citations per year

Countries citing papers authored by Sumit Chopra

Since Specialization
Citations

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

Fields of papers citing papers by Sumit Chopra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Sumit Chopra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sumit Chopra Line = papers co-authored together Sumit Chopra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20250
3 20241
4 202413
5 20241
6 20221
7 202094
8
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
201670
9
The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations
2016144
10
Learning Through Dialogue Interactions.
20164
11
Sequence Level Training with Recurrent Neural Networks
Hit paper breakdown →
2016308
12
Abstractive Sentence Summarization with Attentive Recurrent Neural Networks
Hit paper breakdown →
2016505
13
Learning Longer Memory in Recurrent Neural Networks
201411
14
Question Answering with Subgraph Embeddings
Hit paper breakdown →
2014390
15
DLID: Deep learning for domain adaptation by interpolating between domains
201367
16 20084
17
A Unified Energy-Based Framework for Unsupervised Learning
200753
18 20070
19 20051
20
Learning a Similarity Metric Discriminatively, with Application to Face Verification
Hit paper breakdown →
20052422

About Sumit Chopra

Sumit Chopra is a scholar working on Health Informatics, Family Practice, Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 48 papers that have together received 8.4k indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Natural Language Processing Techniques (9 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Prostate Cancer Diagnosis and Treatment (3 papers), Multimodal Machine Learning Applications (3 papers), Recommender Systems and Techniques (3 papers), Advanced Graph Neural Networks (3 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Health Informatics (301 citations), Computer Vision and Pattern Recognition (4.2k citations), Artificial Intelligence (4.3k citations), Signal Processing (769 citations) and Media Technology (480 citations). Sumit Chopra has collaborated with scholars based in United States, Israel and China. Frequent co-authors include Yann LeCun, Raia Hadsell, Michael Auli, Jason Weston, Alexander M. Rush, Antoine Bordes, Marc’Aurelio Ranzato, Fu Jie Huang, Wojciech Zaremba and Suhrid Balakrishnan. Their work appears in journals such as Alzheimer s & Dementia, Investigative Radiology, Seminars in Ultrasound CT and MRI, Gastrointestinal Endoscopy Clinics of North America and Journal of Parallel and Distributed Computing.

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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