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Journal Articles
- 2023
[j1]Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage, Himabindu Lakkaraju:
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making. Trans. Mach. Learn. Res. 2023 (2023)
Conference and Workshop Papers
- 2019
- [c4]Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir:
Toward Robust Policy Summarization. AAMAS 2019: 2081-2083 - [c3]Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Samuel J. Gershman, Finale Doshi-Velez:
Human Evaluation of Models Built for Interpretability. HCOMP 2019: 59-67 - [c2]Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir:
Exploring Computational User Models for Agent Policy Summarization. IJCAI 2019: 1401-1407 - 2018
- [c1]Isaac Lage, Andrew Slavin Ross, Samuel J. Gershman, Been Kim, Finale Doshi-Velez:
Human-in-the-Loop Interpretability Prior. NeurIPS 2018: 10180-10189
Informal and Other Publications
- 2024
- [i9]Isaac Lage, Sonali Parbhoo, Finale Doshi-Velez:
Towards Integrating Personal Knowledge into Test-Time Predictions. CoRR abs/2406.08636 (2024) - 2022
- [i8]Sanjana Narayanan, Isaac Lage, Finale Doshi-Velez:
(When) Are Contrastive Explanations of Reinforcement Learning Helpful? CoRR abs/2211.07719 (2022) - 2021
- [i7]Anita Mahinpei, Justin Clark, Isaac Lage, Finale Doshi-Velez, Weiwei Pan:
Promises and Pitfalls of Black-Box Concept Learning Models. CoRR abs/2106.13314 (2021) - 2020
- [i6]Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage, Himabindu Lakkaraju:
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making. CoRR abs/2011.06167 (2020) - [i5]Isaac Lage, Finale Doshi-Velez:
Learning Interpretable Concept-Based Models with Human Feedback. CoRR abs/2012.02898 (2020) - 2019
- [i4]Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Sam Gershman, Finale Doshi-Velez:
An Evaluation of the Human-Interpretability of Explanation. CoRR abs/1902.00006 (2019) - [i3]Isaac Lage, Daphna Lifschitz, Finale Doshi-Velez, Ofra Amir:
Exploring Computational User Models for Agent Policy Summarization. CoRR abs/1905.13271 (2019) - 2018
- [i2]Isaac Lage, Andrew Slavin Ross, Been Kim, Samuel J. Gershman, Finale Doshi-Velez:
Human-in-the-Loop Interpretability Prior. CoRR abs/1805.11571 (2018) - [i1]Omer Gottesman, Fredrik D. Johansson, Joshua Meier, Jack Dent, Donghun Lee, Srivatsan Srinivasan, Linying Zhang, Yi Ding, David Wihl, Xuefeng Peng, Jiayu Yao, Isaac Lage, Christopher Mosch, Li-Wei H. Lehman, Matthieu Komorowski, Aldo Faisal, Leo Anthony Celi, David A. Sontag, Finale Doshi-Velez:
Evaluating Reinforcement Learning Algorithms in Observational Health Settings. CoRR abs/1805.12298 (2018)
Coauthor Index
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