Hyunjik Kim

According to our database1, Hyunjik Kim authored at least 22 papers between 2016 and 2023.

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Bibliography

2023
C3: High-performance and low-complexity neural compression from a single image or video.
CoRR, 2023

Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search.
CoRR, 2023

Spatial Functa: Scaling Functa to ImageNet Classification and Generation.
CoRR, 2023

Learning Instance-Specific Augmentations by Capturing Local Invariances.
Proceedings of the International Conference on Machine Learning, 2023

Pre-training via Denoising for Molecular Property Prediction.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Learning Instance-Specific Data Augmentations.
CoRR, 2022

From data to functa: Your data point is a function and you should treat it like one.
CoRR, 2022

From data to functa: Your data point is a function and you can treat it like one.
Proceedings of the International Conference on Machine Learning, 2022

When Does Re-initialization Work?
Proceedings of the Proceedings on "I Can't Believe It's Not Better!, 2022

2021
Group Equivariant Subsampling.
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.
Proceedings of the 38th International Conference on Machine Learning, 2021

LieTransformer: Equivariant Self-Attention for Lie Groups.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Conditional Set Generation with Transformers.
CoRR, 2020

MetaFun: Meta-Learning with Iterative Functional Updates.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Interpretable models in probabilistic machine learning.
PhD thesis, 2019

Meta-Learning surrogate models for sequential decision making.
CoRR, 2019

Attentive Neural Processes.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Disentangling by Factorising.
Proceedings of the 35th International Conference on Machine Learning, 2018

Scaling up the Automatic Statistician: Scalable Structure Discovery using Gaussian Processes.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2016
Tucker Gaussian Process for Regression and Collaborative Filtering.
CoRR, 2016

Scalable Structure Discovery in Regression using Gaussian Processes.
Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016


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