Stefano Ermon
Impact in
- Biophysics top 0.5%
- Automotive Engineering top 1%
- Advanced Battery Technologies Research
Papers in
-
- Generative Adversarial Networks and Image Synthesis 27
-
- Bayesian Modeling and Causal Inference 14
- Domain Adaptation and Few-Shot Learning 12
- Machine Learning and Algorithms 11
- Adversarial Robustness in Machine Learning 11
- Explainable Artificial Intelligence (XAI) 11
- Machine Learning and Data Classification 10
- Anomaly Detection Techniques and Applications 10
- Co-authors
- David B. LobellMarshall BurkeNeal JeanSang Michael XieAditya GroverAnne DriscollSiamak YousefiSankalp Dayal
- Journals
- Science (3 papers)Nature Communications (2 papers)Remote Sensing of Environment (2 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (2 papers)Scientific Reports (1 paper)
- Partner nations
- United StatesChinaCanada
In The Last Decade
Stefano Ermon
135 papers receiving 6.4k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Biophysics 421
- Automotive Engineering 858
- Media Technology 570
- Transportation 432
- Computer Vision and Pattern Recognition 1.1k
Countries citing papers authored by Stefano Ermon
This map shows the geographic impact of Stefano Ermon'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 Stefano Ermon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stefano Ermon more than expected).
Fields of papers citing papers by Stefano Ermon
This network shows the impact of papers produced by Stefano Ermon. 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 Stefano Ermon. The network helps show where Stefano Ermon may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Stefano Ermon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 1 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 2 | |
| 5 | 2023 | 4 | |
| 6 | 2021 | 24 | |
| 7 | Using satellite imagery to understand and promote sustainable development Hit paper breakdown → | 2021 | 257 |
| 8 | Weakly Supervised Disentanglement with Guarantees | 2020 | 7 |
| 9 | 2020 | 83 | |
| 10 | Flexible Approximate Inference via Stratified Normalizing Flows. | 2020 | 1 |
| 11 | Probabilistic Circuits for Variational Inference in Discrete Graphical Models | 2020 | 2 |
| 12 | Sliced Score Matching: A Scalable Approach to Density and Score Estimation | 2019 | 5 |
| 13 | Tile2Vec: Unsupervised representation learning for remote sensing data | 2018 | 2 |
| 14 | Flow-GAN: Bridging implicit and prescribed learning in generative models. | 2017 | 3 |
| 15 | InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations | 2017 | 47 |
| 16 | Generative Adversarial Learning of Markov Chains | 2017 | 0 |
| 17 | Adaptive Concentration Inequalities for Sequential Decision Problems | 2016 | 11 |
| 18 | Variable elimination in the Fourier domain | 2016 | 2 |
| 19 | Embed and Project: Discrete Sampling with Universal Hashing | 2013 | 34 |
| 20 | 2011 | 1 |
About Stefano Ermon
Stefano Ermon is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mathematics, Signal Processing and Modeling and Simulation, having authored 143 papers that have together received 6.6k indexed citations. Recurring topics across this work include Generative Adversarial Networks and Image Synthesis (27 papers), Bayesian Modeling and Causal Inference (14 papers), Domain Adaptation and Few-Shot Learning (12 papers), Machine Learning and Algorithms (11 papers), Adversarial Robustness in Machine Learning (11 papers), Explainable Artificial Intelligence (XAI) (11 papers), Machine Learning and Data Classification (10 papers) and Anomaly Detection Techniques and Applications (10 papers). The work is most often cited by research in Biophysics (421 citations), Automotive Engineering (858 citations), Media Technology (570 citations), Transportation (432 citations) and Computer Vision and Pattern Recognition (1.1k citations). Stefano Ermon has collaborated with scholars based in United States, China and Canada. Frequent co-authors include David B. Lobell, Marshall Burke, Neal Jean, Sang Michael Xie, Aditya Grover, Anne Driscoll, Siamak Yousefi, Sankalp Dayal, Shahrokh Valaee and Shengjia Zhao. Their work appears in journals such as Science, Nature Communications, Remote Sensing of Environment, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.
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.