Sven Gowal

2.8k citations
26 papers · 664 indexed · 2 hit papers · h-index 9
Topics
Adversarial Robustness in Machine Learning (11 papers)Distributed Control Multi-Agent Systems (6 papers)Reinforcement Learning in Robotics (5 papers)
Journals
Nature MedicineMachine LearningInfoscience (Ecole Polytechnique Fédérale de Lausanne)

In The Last Decade

Sven Gowal

26 papers receiving 642 citations

Hit Papers

Challenges of real-world reinforcement learning: definiti...202120262022202420212024100200300

Peers

Sven Gowal
Comparison fields: 5 of 88
  • Artificial Intelligence 362
  • Control and Systems Engineering 139
  • Computer Vision and Pattern Recognition 100
  • Electrical and Electronic Engineering 94
  • Computer Networks and Communications 87
Replace Zhuangdi Zhu with:
Zhuangdi Zhu United States
Antonio Berlanga Spain
Zuobin Ying China
Gaolei Li China
Subrota Kumar Mondal Macao
Yuqi Fan China
Jian Peng China
TaeChoong Chung South Korea
Myeonghwi Kim South Korea
Sven Gowal relative to Zhuangdi Zhu United States Zhuangdi Zhu's profile →
Citations per field
00.5×
Zhuangdi Zhu · 1×
Citations per year

Countries citing papers authored by Sven Gowal

Since Specialization
Citations

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

Fields of papers citing papers by Sven Gowal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sven Gowal

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1
Generative models improve fairness of medical classifiers under distribution shiftsbreakdown →
55
2 2
3
Self-supervised Adversarial Robustness for the Low-label, High-data Regime
6
4 2
5
Challenges of real-world reinforcement learning: definitions, benchmarks and analysisbreakdown →
320
6
Towards Verified Robustness under Text Deletion Interventions
3
7
Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control
8
8
A FRAMEWORK FOR ROBUSTNESS CERTIFICATION OF SMOOTHED CLASSIFIERS USING F-DIVERGENCES
4
9 7
10 64
11
Efficient Neural Network Verification with Exactness Characterization
8
12
Adversarial Robustness through Local Linearization
27
13 64
14 3
15
Learning from Delayed Outcomes with Intermediate Observations
3
16 2
17 3
18 5
19 8
20 7

About Sven Gowal

Sven Gowal is a scholar working on Artificial Intelligence, Hardware and Architecture and Instrumentation, having authored 26 papers that have together received 664 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (11 papers), Distributed Control Multi-Agent Systems (6 papers) and Reinforcement Learning in Robotics (5 papers). The work is most often cited by research in Health Informatics (22 citations), Artificial Intelligence (362 citations) and Control and Systems Engineering (139 citations). Sven Gowal has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Daniel J. Mankowitz, Cosmin Păduraru, Todd Hester, Jerry Li, Nir Levine, Gabriel Dulac-Arnold, Pushmeet Kohli, Alcherio Martinoli, Krishnamurthy Dvijotham and Robert Stanforth. Their work appears in journals such as Nature Medicine, Machine Learning and Infoscience (Ecole Polytechnique Fédérale de Lausanne).

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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