Logan Engstrom

46 papers A* 17Journal 27Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	DataMIL: Selecting Data for Robot Imitation Learning with Datamodels. CoRR Shivin Dass, Alaa Khaddaj, Logan Engstrom, Aleksander Madry, Andrew Ilyas, Roberto Martín-Martín
2025	J	`jnl`	MAGIC: Near-Optimal Data Attribution for Deep Learning. CoRR Andrew Ilyas, Logan Engstrom
2025	J	`jnl`	Optimizing ML Training with Metagradient Descent. CoRR Logan Engstrom, Andrew Ilyas, Benjamin Chen, Axel Feldmann, William Moses, Aleksander Madry
2025	J	`jnl`	Small-to-Large Generalization: Data Influences Models Consistently Across Scale. CoRR Alaa Khaddaj, Logan Engstrom, Aleksander Madry
2025	A*	`conf`	Small-to-Large Generalization: Training Data Influences Models Consistently Across Scale. ICLR Alaa Khaddaj, Logan Engstrom, Aleksander Madry
2024	A*	`conf`	DsDm: Model-Aware Dataset Selection with Datamodels. ICML Logan Engstrom, Axel Feldmann, Aleksander Madry
2024	J	`jnl`	DsDm: Model-Aware Dataset Selection with Datamodels. CoRR Logan Engstrom, Axel Feldmann, Aleksander Madry
2023	J	`jnl`	Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation. CoRR Joshua Vendrow, Saachi Jain, Logan Engstrom, Aleksander Madry
2023	A*	`conf`	FFCV: Accelerating Training by Removing Data Bottlenecks. CVPR Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry
2023	J	`jnl`	FFCV: Accelerating Training by Removing Data Bottlenecks. CoRR Guillaume Leclerc, Andrew Ilyas, Logan Engstrom, Sung Min Park, Hadi Salman, Aleksander Madry
2022	A*	`conf`	3DB: A Framework for Debugging Computer Vision Models. NeurIPS Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry
2022	J	`jnl`	Datamodels: Predicting Predictions from Training Data. CoRR Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry
2022	A*	`conf`	Datamodels: Understanding Predictions with Data and Data with Predictions. ICML Andrew Ilyas, Sung Min Park, Logan Engstrom, Guillaume Leclerc, Aleksander Madry
2022	J	`jnl`	When does Bias Transfer in Transfer Learning? CoRR Hadi Salman, Saachi Jain, Andrew Ilyas, Logan Engstrom, Eric Wong, Aleksander Madry
2021	J	`jnl`	3DB: A Framework for Debugging Computer Vision Models. CoRR Guillaume Leclerc, Hadi Salman, Andrew Ilyas, Sai Vemprala, Logan Engstrom, Vibhav Vineet, Kai Yuanqing Xiao, Pengchuan Zhang, Shibani Santurkar, Greg Yang, Ashish Kapoor, Aleksander Madry
2021	A*	`conf`	Noise or Signal: The Role of Image Backgrounds in Object Recognition. ICLR Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry
2021	A*	`conf`	Unadversarial Examples: Designing Objects for Robust Vision. NeurIPS Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor
2020	A*	`conf`	A Closer Look at Deep Policy Gradients. ICLR Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
2020	A*	`conf`	Do Adversarially Robust ImageNet Models Transfer Better? NeurIPS Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry
2020	J	`jnl`	Do Adversarially Robust ImageNet Models Transfer Better? CoRR Hadi Salman, Andrew Ilyas, Logan Engstrom, Ashish Kapoor, Aleksander Madry
2020	A*	`conf`	From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. ICML Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry
2020	J	`jnl`	From ImageNet to Image Classification: Contextualizing Progress on Benchmarks. CoRR Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Andrew Ilyas, Aleksander Madry
2020	A*	`conf`	Identifying Statistical Bias in Dataset Replication. ICML Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry
2020	J	`jnl`	Identifying Statistical Bias in Dataset Replication. CoRR Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Jacob Steinhardt, Aleksander Madry
2020	J	`jnl`	Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO. CoRR Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
2020	A*	`conf`	Implementation Matters in Deep RL: A Case Study on PPO and TRPO. ICLR Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
2020	J	`jnl`	Noise or Signal: The Role of Image Backgrounds in Object Recognition. CoRR Kai Yuanqing Xiao, Logan Engstrom, Andrew Ilyas, Aleksander Madry
2020	J	`jnl`	Unadversarial Examples: Designing Objects for Robust Vision. CoRR Hadi Salman, Andrew Ilyas, Logan Engstrom, Sai Vemprala, Aleksander Madry, Ashish Kapoor
2019	A*	`conf`	Adversarial Examples Are Not Bugs, They Are Features. NeurIPS Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry
2019	J	`jnl`	Adversarial Examples Are Not Bugs, They Are Features. CoRR Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry
2019	J	`jnl`	Computer Vision with a Single (Robust) Classifier. CoRR Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Andrew Ilyas, Logan Engstrom, Aleksander Madry
2019	A*	`conf`	Exploring the Landscape of Spatial Robustness. ICML Logan Engstrom, Brandon Tran, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry
2019	A*	`conf`	Image Synthesis with a Single (Robust) Classifier. NeurIPS Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, Aleksander Madry
2019	J	`jnl`	Learning Perceptually-Aligned Representations via Adversarial Robustness. CoRR Logan Engstrom, Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Brandon Tran, Aleksander Madry
2019	—	`conf`	Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors. ICLR (Poster) Andrew Ilyas, Logan Engstrom, Aleksander Madry
2019	—	`conf`	Robustness May Be at Odds with Accuracy. ICLR (Poster) Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry
2018	J	`jnl`	Are Deep Policy Gradient Algorithms Truly Policy Gradient Algorithms? CoRR Andrew Ilyas, Logan Engstrom, Shibani Santurkar, Dimitris Tsipras, Firdaus Janoos, Larry Rudolph, Aleksander Madry
2018	A*	`conf`	Black-box Adversarial Attacks with Limited Queries and Information. ICML Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin
2018	J	`jnl`	Black-box Adversarial Attacks with Limited Queries and Information. CoRR Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin
2018	J	`jnl`	Evaluating and Understanding the Robustness of Adversarial Logit Pairing. CoRR Logan Engstrom, Andrew Ilyas, Anish Athalye
2018	J	`jnl`	Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors. CoRR Andrew Ilyas, Logan Engstrom, Aleksander Madry
2018	A*	`conf`	Synthesizing Robust Adversarial Examples. ICML Anish Athalye, Logan Engstrom, Andrew Ilyas, Kevin Kwok
2018	J	`jnl`	There Is No Free Lunch In Adversarial Robustness (But There Are Unexpected Benefits). CoRR Dimitris Tsipras, Shibani Santurkar, Logan Engstrom, Alexander Turner, Aleksander Madry
2017	J	`jnl`	A Rotation and a Translation Suffice: Fooling CNNs with Simple Transformations. CoRR Logan Engstrom, Dimitris Tsipras, Ludwig Schmidt, Aleksander Madry
2017	J	`jnl`	Query-Efficient Black-box Adversarial Examples. CoRR Andrew Ilyas, Logan Engstrom, Anish Athalye, Jessy Lin
2017	J	`jnl`	Synthesizing Robust Adversarial Examples. CoRR Anish Athalye, Logan Engstrom, Andrew Ilyas, Kevin Kwok