Arjun Krishnakumar

According to our database, Arjun Krishnakumar authored at least 10 papers between 2021 and 2026.

Collaborative distances:

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

2026

Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch.

Fabio Ferreira, Lucca Wobbe, Arjun Krishnakumar, Frank Hutter, Arber Zela

CoRR, March, 2026

2025

Where to Begin: Efficient Pretraining via Subnetwork Selection and Distillation.

Arjun Krishnakumar, Rhea Sanjay Sukthanker, Hannan Javed Mahadik, Gabriela Kadlecová, Vladyslav Moroshan, Timur Carstensen, Frank Hutter, Aaron Klein

CoRR, October, 2025

confopt: A Library for Implementation and Evaluation of Gradient-based One-Shot NAS Methods.

Abhash Kumar Jha, Shakiba Moradian, Arjun Krishnakumar, Martin Rapp, Frank Hutter

CoRR, July, 2025

Accurate predictions on small data with a tabular foundation model.

Noah Hollmann, Samuel Müller, Lennart Purucker, Arjun Krishnakumar, Max Körfer, Shi Bin Hoo, Robin Tibor Schirrmeister, Frank Hutter

Nat., January, 2025

\textttconfopt: A Library for Implementation and Evaluation of Gradient-based One-Shot NAS Methods.

Abhash Kumar Jha, Shakiba Moradian, Arjun Krishnakumar, Martin Rapp, Frank Hutter

Proceedings of the International Conference on Automated Machine Learning (AutoML 2025), 2025

2024

TabPFN.

Noah Hollmann, Frank Hutter, Samuel Gabriel Müller, Lennart Purucker, Arjun Krishnakumar, Max Körfer, Robin Tibor Schirrmeister

Dataset, October, 2024

Weight-Entanglement Meets Gradient-Based Neural Architecture Search.

Rhea Sanjay Sukthanker, Arjun Krishnakumar, Mahmoud Safari, Frank Hutter

Proceedings of the International Conference on Automated Machine Learning, 2024

2022

NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies.

Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari, Frank Hutter

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

NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy.

Yash Mehta, Colin White, Arber Zela, Arjun Krishnakumar, Guri Zabergja, Shakiba Moradian, Mahmoud Safari, Kaicheng Yu, Frank Hutter

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

AutoML Decathlon: Diverse Tasks, Modern Methods, and Efficiency at Scale.

Nicholas Roberts, Samuel Guo, Cong Xu, Ameet Talwalkar, David Lander, Lvfang Tao, Linhang Cai, Shuaicheng Niu, Jianyu Heng, Hongyang Qin, Minwen Deng, Johannes Hog, Alexander Pfefferle, Sushil Ammanaghatta Shivakumar, Arjun Krishnakumar, Yubo Wang, Rhea Sanjay Sukthanker, Frank Hutter, Euxhen Hasanaj, Tien-Dung Le, Mikhail Khodak, Yuriy Nevmyvaka, Kashif Rasul, Frederic Sala, Anderson Schneider, Junhong Shen, Evan Randall Sparks

Proceedings of the NeurIPS 2022 Competition Track, 2021