Henrik Marklund

According to our database, Henrik Marklund authored at least 16 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Consequentialist Objectives and Catastrophe.

Henrik Marklund, Alex Infanger, Benjamin Van Roy

CoRR, March, 2026

Inference-Time Alignment via Hypothesis Reweighting.

Yoonho Lee, Jonathan Williams, Henrik Marklund, Archit Sharma, Eric Mitchell, Anikait Singh, Chelsea Finn

Trans. Mach. Learn. Res., 2026

Misalignment from Treating Means as Ends.

Henrik Marklund, Alex Infanger, Benjamin Van Roy

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Granular feedback merits sophisticated aggregation.

Anmol Kagrecha, Henrik Marklund, Potsawee Manakul, Richard Zeckhauser, Benjamin Van Roy

CoRR, July, 2025

Continual Learning as Computationally Constrained Reinforcement Learning.

Saurabh Kumar, Henrik Marklund, Ashish Rao, Yifan Zhu, Hong Jun Jeon, Yueyang Liu, Benjamin Van Roy

Found. Trends Mach. Learn., 2025

2024

Test-Time Alignment via Hypothesis Reweighting.

Yoonho Lee, Jonathan Williams, Henrik Marklund, Archit Sharma, Eric Mitchell, Anikait Singh, Chelsea Finn

CoRR, 2024

Choice between Partial Trajectories.

Henrik Marklund, Benjamin Van Roy

CoRR, 2024

Adaptive Crowdsourcing Via Self-Supervised Learning.

Anmol Kagrecha, Henrik Marklund, Benjamin Van Roy, Hong Jun Jeon, Richard Zeckhauser

CoRR, 2024

Maintaining Plasticity in Continual Learning via Regenerative Regularization.

Saurabh Kumar, Henrik Marklund, Benjamin Van Roy

Proceedings of the Conference on Lifelong Learning Agents, 2024

2023

Maintaining Plasticity via Regenerative Regularization.

Saurabh Kumar, Henrik Marklund, Benjamin Van Roy

CoRR, 2023

2022

Extending the WILDS Benchmark for Unsupervised Adaptation.

Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Adaptive Risk Minimization: Learning to Adapt to Domain Shift.

Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn

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

WILDS: A Benchmark of in-the-Wild Distribution Shifts.

Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran S. Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

WILDS: A Benchmark of in-the-Wild Distribution Shifts.

Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang

CoRR, 2020

Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift.

Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn

CoRR, 2020

2019

CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison.

Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher Chute, Henrik Marklund, Behzad Haghgoo, Robyn L. Ball, Katie S. Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019