Logan Engstrom

According to our database1, Logan Engstrom authored at least 29 papers between 2017 and 2024.

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Bibliography

2024
DsDm: Model-Aware Dataset Selection with Datamodels.
CoRR, 2024

2023
Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation.
CoRR, 2023

FFCV: Accelerating Training by Removing Data Bottlenecks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
When does Bias Transfer in Transfer Learning?
CoRR, 2022

Datamodels: Predicting Predictions from Training Data.
CoRR, 2022

3DB: A Framework for Debugging Computer Vision Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Datamodels: Understanding Predictions with Data and Data with Predictions.
Proceedings of the International Conference on Machine Learning, 2022

2021
Unadversarial Examples: Designing Objects for Robust Vision.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Noise or Signal: The Role of Image Backgrounds in Object Recognition.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO.
CoRR, 2020

Do Adversarially Robust ImageNet Models Transfer Better?
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

From ImageNet to Image Classification: Contextualizing Progress on Benchmarks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Identifying Statistical Bias in Dataset Replication.
Proceedings of the 37th International Conference on Machine Learning, 2020

A Closer Look at Deep Policy Gradients.
Proceedings of the 8th International Conference on Learning Representations, 2020

Implementation Matters in Deep RL: A Case Study on PPO and TRPO.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Computer Vision with a Single (Robust) Classifier.
CoRR, 2019

Learning Perceptually-Aligned Representations via Adversarial Robustness.
CoRR, 2019

Image Synthesis with a Single (Robust) Classifier.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Adversarial Examples Are Not Bugs, They Are Features.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Exploring the Landscape of Spatial Robustness.
Proceedings of the 36th International Conference on Machine Learning, 2019

Robustness May Be at Odds with Accuracy.
Proceedings of the 7th International Conference on Learning Representations, 2019

Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms?
CoRR, 2018

Evaluating and Understanding the Robustness of Adversarial Logit Pairing.
CoRR, 2018

There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits).
CoRR, 2018

Black-box Adversarial Attacks with Limited Queries and Information.
Proceedings of the 35th International Conference on Machine Learning, 2018

Synthesizing Robust Adversarial Examples.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Query-Efficient Black-box Adversarial Examples.
CoRR, 2017

A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations.
CoRR, 2017


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