Sven Gowal
28 papers · 2019–2025 · 10 conferences · across top CS/AI conferences
Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot (10) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🏃 Academic Marathon (6)
🧭
Keyword Pioneer
🐣
Hot Topic Early Bird
🐝
Cross-Pollinator
(12)
🤝
Dynamic Duo
(13)
👑
Triple Crown
🔬
Deep Specialist
(10)
🏆
Keyword Champion
(3)
🚀
Conference Pioneer
🗃️
Keyword Collector
(60)
⚡
Prolific Year
(6)
🔥
Unstoppable
(7)
💎
Century Club
(28)
Conferences
ICLR (9)
NIPS (6)
ICML (4)
CVPR (3)
AISTATS (1)
EMNLP (1)
ICCV (1)
IJCAI (1)
IJCNLP (1)
UAI (1)
Top co-authors
Keywords
adversarial robustness
(14)
adversarial training
(5)
formal verification
(4)
adversarial attack
(4)
neural network verification
(4)
interval bound propagation
(3)
data augmentation
(3)
image classification
(3)
model robustness
(2)
lagrangian relaxation
(2)
neural network
(2)
text classification
(2)
generative model
(2)
verified accuracy
(2)
symbol substitution
(2)
content moderation
(1)
domain generalization
(1)
attention mechanism
(1)
online learning
(1)
self-supervised learning
(1)
Papers
On the Difficulty of Constructing a Robust and Publicly-Detectable Watermark
AISTATS 2025
Evaluating Model Bias Requires Characterizing its Mistakes
ICML 2024
Seasoning Model Soups for Robustness to Adversarial and Natural Distribution Shifts
CVPR 2023
Revisiting adapters with adversarial training
ICLR 2023
Benchmarking Robustness to Adversarial Image Obfuscations
NIPS 2023
Defending Against Image Corruptions Through Adversarial Augmentations
ICLR 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
ICML 2022
Hindering Adversarial Attacks with Implicit Neural Representations
ICML 2022
A Fine-Grained Analysis on Distribution Shift
ICLR 2022
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications
NIPS 2021
Data Augmentation Can Improve Robustness
NIPS 2021
Self-supervised Adversarial Robustness for the Low-label, High-data Regime
ICLR 2021
Improving Robustness using Generated Data
NIPS 2021
Towards Stable and Efficient Training of Verifiably Robust Neural Networks
ICLR 2020
Achieving Robustness in the Wild via Adversarial Mixing With Disentangled Representations
CVPR 2020
Towards Robust Image Classification Using Sequential Attention Models
CVPR 2020
The Autoencoding Variational Autoencoder
NIPS 2020
A FRAMEWORK FOR ROBUSTNESS CERTIFICATION OF SMOOTHED CLASSIFIERS USING F-DIVERGENCES
ICLR 2020
Towards Verified Robustness under Text Deletion Interventions
ICLR 2020
Efficient Neural Network Verification with Exactness Characterization
UAI 2019
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation
EMNLP 2019
Scalable Verified Training for Provably Robust Image Classification
ICCV 2019
Beyond Greedy Ranking: Slate Optimization via List-CVAE
ICLR 2019
Verification of Non-Linear Specifications for Neural Networks
ICLR 2019
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
ICML 2019
A Dual Approach to Verify and Train Deep Networks
IJCAI 2019
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation
IJCNLP 2019
Adversarial Robustness through Local Linearization
NIPS 2019