Chad Martin

According to our database, Chad Martin authored at least 3 papers between 2020 and 2024.

Collaborative distances:

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

2024

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets.

Dominique Beaini, Shenyang Huang, Joao Alex Cunha, Zhiyi Li, Gabriela Moisescu-Pareja, Oleksandr Dymov, Samuel Maddrell-Mander, Callum McLean, Frederik Wenkel, Luis Müller, Jama Hussein Mohamud, Ali Parviz, Michael Craig, Michal Koziarski, Jiarui Lu, Zhaocheng Zhu, Cristian Gabellini, Kerstin Klaser, Josef Dean, Cas Wognum, Maciej Sypetkowski, Guillaume Rabusseau, Reihaneh Rabbany, Jian Tang, Christopher Morris, Ioannis Koutis, Mirco Ravanelli, Guy Wolf, Prudencio Tossou, Hadrien Mary, Therence Bois, Andrew W. Fitzgibbon, Blazej Banaszewski, Chad Martin, Dominic Masters

CoRR, 2023

2020

Addressing the Memory Bottleneck in AI Model Training.

David Ojika, Bhavesh Patel, G. Anthony Reina, Trent Boyer, Chad Martin, Prashant Shah

CoRR, 2020