# Stefano Ermon

**Type:** Researchers  
**Canonical URL:** https://scholariq.org/researchers/stefano-ermon/

## Facts

| Field | Value |
| --- | --- |
| Citations | 25,946 |
| Field | Generative Adversarial Networks and Image Synthesis |
| h-index | 66 |
| i10-index | 196 |
| Last Known Institution | Stanford University |
| OpenAlex ID | https://openalex.org/A5091179481 |
| ORCID iD | https://orcid.org/0000-0003-0039-2887 |
| Works | 479 |

## Researcher papers

- [Score-Based Generative Modeling through Stochastic Differential Equations](https://scholariq.org/papers/score-based-generative-modeling-through-stochastic-differential-equations/)
- [Sequence modeling and design from molecular to genome scale with Evo](https://scholariq.org/papers/sequence-modeling-and-design-from-molecular-to-genome-scale-with-evo-2/)
- [High‐Voltage Charging‐Induced Strain, Heterogeneity, and Micro‐Cracks in Secondary Particles of a Nickel‐Rich Layered Cathode Material](https://scholariq.org/papers/high-voltage-charging-induced-strain-heterogeneity-and-micro-cracks-in-secondary/)

## Researcher topics

- [Generative Adversarial Networks and Image Synthesis](https://scholariq.org/topics/generative-adversarial-networks-and-image-synthesis/)
- [Domain Adaptation and Few-Shot Learning](https://scholariq.org/topics/domain-adaptation-and-few-shot-learning/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling-2/)
- [Model Reduction and Neural Networks](https://scholariq.org/topics/model-reduction-and-neural-networks/)

## Researcher university

- [Stanford University](https://scholariq.org/institutions/stanford-university/)

---
Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.