Conor Durkan

According to our database, Conor Durkan authored at least 10 papers between 2018 and 2023.

Collaborative distances:

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

2023

Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC.

Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Sussman Grathwohl

Proceedings of the International Conference on Machine Learning, 2023

2022

Continuous diffusion for categorical data.

Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler

CoRR, 2022

2021

On Maximum Likelihood Training of Score-Based Generative Models.

Conor Durkan, Yang Song

CoRR, 2021

Maximum Likelihood Training of Score-Based Diffusion Models.

Yang Song, Conor Durkan, Iain Murray, Stefano Ermon

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

2020

sbi: A toolkit for simulation-based inference.

Álvaro Tejero-Cantero, Jan Boelts, Michael Deistler, Jan-Matthis Lueckmann, Conor Durkan, Pedro J. Gonçalves, David S. Greenberg, Jakob H. Macke

J. Open Source Softw., 2020

On Contrastive Learning for Likelihood-free Inference.

Conor Durkan, Iain Murray, George Papamakarios

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Cubic-Spline Flows.

Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios

CoRR, 2019

Neural Spline Flows.

Conor Durkan, Artur Bekasov, Iain Murray, George Papamakarios

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

Autoregressive Energy Machines.

Conor Durkan, Charlie Nash

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

2018

Sequential Neural Methods for Likelihood-free Inference.

Conor Durkan, George Papamakarios, Iain Murray

CoRR, 2018