Emilien Dupont

According to our database, Emilien Dupont authored at least 19 papers between 2018 and 2024.

Collaborative distances:

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

2024

Mathematical discoveries from program search with large language models.

Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi

Nat., January, 2024

2023

C3: High-performance and low-complexity neural compression from a single image or video.

Hyunjik Kim, Matthias Bauer, Lucas Theis, Jonathan Richard Schwarz, Emilien Dupont

CoRR, 2023

Spatial Functa: Scaling Functa to ImageNet Classification and Generation.

Matthias Bauer, Emilien Dupont, Andy Brock, Dan Rosenbaum, Jonathan Schwarz, Hyunjik Kim

CoRR, 2023

Deep Stochastic Processes via Functional Markov Transition Operators.

Jin Xu, Emilien Dupont, Kaspar Märtens, Thomas Rainforth, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

COIN++: Neural Compression Across Modalities.

Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet

Trans. Mach. Learn. Res., 2022

COIN++: Data Agnostic Neural Compression.

Emilien Dupont, Hrushikesh Loya, Milad Alizadeh, Adam Golinski, Yee Whye Teh, Arnaud Doucet

CoRR, 2022

From data to functa: Your data point is a function and you should treat it like one.

Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo J. Rezende, Dan Rosenbaum

CoRR, 2022

From data to functa: Your data point is a function and you can treat it like one.

Emilien Dupont, Hyunjik Kim, S. M. Ali Eslami, Danilo Jimenez Rezende, Dan Rosenbaum

Proceedings of the International Conference on Machine Learning, 2022

Generative Models as Distributions of Functions.

Emilien Dupont, Yee Whye Teh, Arnaud Doucet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

COIN: COmpression with Implicit Neural representations.

Emilien Dupont, Adam Golinski, Milad Alizadeh, Yee Whye Teh, Arnaud Doucet

CoRR, 2021

LieTransformer: Equivariant Self-Attention for Lie Groups.

Michael J. Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim

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

2020

STEER : Simple Temporal Regularization For Neural ODEs.

Arnab Ghosh, Harkirat Singh Behl, Emilien Dupont, Philip H. S. Torr, Vinay P. Namboodiri

CoRR, 2020

Equivariant Neural Rendering.

Emilien Dupont, Miguel Ángel Bautista, Alex Colburn, Aditya Sankar, Carlos Guestrin, Josh M. Susskind, Qi Shan

CoRR, 2020

STEER : Simple Temporal Regularization For Neural ODE.

Arnab Ghosh, Harkirat S. Behl, Emilien Dupont, Philip H. S. Torr, Vinay P. Namboodiri

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Equivariant Neural Rendering.

Emilien Dupont, Miguel Bautista Martin, Alex Colburn, Aditya Sankar, Josh M. Susskind, Qi Shan

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

2019

Augmented Neural ODEs.

Emilien Dupont, Arnaud Doucet, Yee Whye Teh

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

Probabilistic Semantic Inpainting with Pixel Constrained CNNs.

Emilien Dupont, Suhas Suresha

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Joint-VAE: Learning Disentangled Joint Continuous and Discrete Representations.

Emilien Dupont

CoRR, 2018

Learning Disentangled Joint Continuous and Discrete Representations.

Emilien Dupont

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018