Hyunjik Kim

According to our database, Hyunjik Kim authored at least 23 papers between 2016 and 2024.

Collaborative distances:

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

2024

Neural Compression of Atmospheric States.

Piotr Mirowski, David Warde-Farley, Mihaela Rosca, Matthew Koichi Grimes, Yana Hasson, Hyunjik Kim, Mélanie Rey, Simon Osindero, Suman V. Ravuri, Shakir Mohamed

CoRR, 2024

Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search.

Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Matej Balog, Gheorghe Comanici, Tudor Berariu, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera-Paredes, Petar Velickovic, Laurent Orseau, Joonkyung Lee, Anurag Murty Naredla, Doina Precup, Adam Zsolt Wagner

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Spatial Functa: Scaling Functa to ImageNet Classification and Generation.

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

CoRR, 2023

Learning Instance-Specific Augmentations by Capturing Local Invariances.

Ning Miao, Tom Rainforth, Emile Mathieu, Yann Dubois, Yee Whye Teh, Adam Foster, Hyunjik Kim

Proceedings of the International Conference on Machine Learning, 2023

Pre-training via Denoising for Molecular Property Prediction.

Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Learning Instance-Specific Data Augmentations.

Ning Miao, Emile Mathieu, Yann Dubois, Tom Rainforth, Yee Whye Teh, Adam Foster, Hyunjik Kim

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

When Does Re-initialization Work?

Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu

Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022

2021

Group Equivariant Subsampling.

Jin Xu, Hyunjik Kim, Thomas Rainforth, Yee Whye Teh

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

The Lipschitz Constant of Self-Attention.

Hyunjik Kim, George Papamakarios, Andriy Mnih

Proceedings of the 38th International Conference on Machine Learning, 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

Conditional Set Generation with Transformers.

Adam R. Kosiorek, Hyunjik Kim, Danilo J. Rezende

CoRR, 2020

MetaFun: Meta-Learning with Iterative Functional Updates.

Jin Xu, Jean-Francois Ton, Hyunjik Kim, Adam R. Kosiorek, Yee Whye Teh

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

2019

Interpretable models in probabilistic machine learning.

Hyunjik Kim

PhD thesis, 2019

Meta-Learning surrogate models for sequential decision making.

Alexandre Galashov, Jonathan Schwarz, Hyunjik Kim, Marta Garnelo, David Saxton, Pushmeet Kohli, S. M. Ali Eslami, Yee Whye Teh

CoRR, 2019

Attentive Neural Processes.

Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, S. M. Ali Eslami, Dan Rosenbaum, Oriol Vinyals, Yee Whye Teh

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects.

Adam R. Kosiorek, Hyunjik Kim, Yee Whye Teh, Ingmar Posner

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

Disentangling by Factorising.

Hyunjik Kim, Andriy Mnih

Proceedings of the 35th International Conference on Machine Learning, 2018

Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes.

Hyunjik Kim, Yee Whye Teh

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2016

Tucker Gaussian Process for Regression and Collaborative Filtering.

Hyunjik Kim, Xiaoyu Lu, Seth R. Flaxman, Yee Whye Teh

CoRR, 2016

Scalable Structure Discovery in Regression using Gaussian Processes.

Hyunjik Kim, Yee Whye Teh

Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016