Yoonho Lee

Orcid: 0000-0002-5146-5444

Affiliations:

Stanford University, CA, USA
AITRICS, Seoul, Korea (former)

According to our database¹, Yoonho Lee authored at least 25 papers between 2018 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning.

[BibT_eX]

[DOI]

CoRR, 2024

Clarify: Improving Model Robustness With Natural Language Corrections.

[BibT_eX]

[DOI]

CoRR, 2024

AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data.

[BibT_eX]

[DOI]

CoRR, 2024

2023

Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts.

[BibT_eX]

[DOI]

CoRR, 2023

Conservative Prediction via Data-Driven Confidence Minimization.

[BibT_eX]

[DOI]

CoRR, 2023

Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.

[BibT_eX]

[DOI]

CoRR, 2023

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature.

[BibT_eX]

[DOI]

Eric Mitchell

Yoonho Lee

Alexander Khazatsky

Christopher D. Manning

Chelsea Finn

Proceedings of the International Conference on Machine Learning, 2023

Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement.

[BibT_eX]

[DOI]

Yoonho Lee

Huaxiu Yao

Chelsea Finn

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Discrete Infomax Codes for Supervised Representation Learning.

[BibT_eX]

[DOI]

Entropy, 2022

Diversify and Disambiguate: Learning From Underspecified Data.

[BibT_eX]

[DOI]

Yoonho Lee

Huaxiu Yao

Chelsea Finn

CoRR, 2022

Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On Divergence Measures for Bayesian Pseudocoresets.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

On the distribution of penultimate activations of classification networks.

[BibT_eX]

[DOI]

Minkyo Seo

Yoonho Lee

Suha Kwak

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Diversity Matters When Learning From Ensembles.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Attentive Clustering Processes.

[BibT_eX]

[DOI]

CoRR, 2020

Bootstrapping neural processes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Neural Complexity Measures.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Deep Amortized Clustering.

[BibT_eX]

[DOI]

Juho Lee

Yoonho Lee

Yee Whye Teh

CoRR, 2019

Discrete Infomax Codes for Meta-Learning.

[BibT_eX]

[DOI]

Yoonho Lee

Wonjae Kim

Seungjin Choi

CoRR, 2019

Learning Dynamics of Attention: Human Prior for Interpretable Machine Reasoning.

[BibT_eX]

[DOI]

Wonjae Kim

Yoonho Lee

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Set Transformer.

[BibT_eX]

[DOI]

CoRR, 2018

Meta-Learning with Adaptive Layerwise Metric and Subspace.

[BibT_eX]

[DOI]

Yoonho Lee

Seungjin Choi

CoRR, 2018

Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace.

[BibT_eX]

[DOI]

Yoonho Lee

Seungjin Choi

Proceedings of the 35th International Conference on Machine Learning, 2018

Yoonho Lee

Timeline

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