Andrew N. Carr

According to our database, Andrew N. Carr authored at least 4 papers between 2019 and 2021.

Collaborative distances:

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

2021

Self-Supervised Learning of Audio Representations From Permutations With Differentiable Ranking.

Andrew N. Carr, Quentin Berthet, Mathieu Blondel, Olivier Teboul, Neil Zeghidour

IEEE Signal Process. Lett., 2021

Evaluating Large Language Models Trained on Code.

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Joshua Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, Wojciech Zaremba

CoRR, 2021

2019

Wasserstein Neural Processes.

Andrew N. Carr, Jared Nielson, David Wingate

CoRR, 2019

Graph Neural Processes: Towards Bayesian Graph Neural Networks.

Andrew N. Carr, David Wingate

CoRR, 2019