Kim, Hyunjik

19 publications

ICLR 2026 MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer Yanghao Li, Rui Qian, Bowen Pan, Haotian Zhang, Haoshuo Huang, Bowen Zhang, Jialing Tong, Haoxuan You, Xianzhi Du, Zhe Gan, Hyunjik Kim, Chao Jia, Zhenbang Wang, Yinfei Yang, Mingfei Gao, Zi-Yi Dou, Wenze Hu, Chang Gao, Dongxu Li, Philipp Dufter, Zirui Wang, Guoli Yin, Zhengdong Zhang, Chen Chen, Yang Zhao, Ruoming Pang, Zhifeng Chen

CVPR 2025 Good, Cheap, and Fast: Overfitted Image Compression with Wasserstein Distortion Jona Ballé, Luca Versari, Emilien Dupont, Hyunjik Kim, Matthias Bauer

CVPR 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

IJCAI 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

NeurIPSW 2023 Finding Increasingly Large Extremal Graphs with AlphaZero and Tabu Search Abbas Mehrabian, Ankit Anand, Hyunjik Kim, Nicolas Sonnerat, Tudor Berariu, Matej Balog, Gheorghe Comanici, Andrew Lee, Anian Ruoss, Anna Bulanova, Daniel Toyama, Sam Blackwell, Bernardino Romera Paredes, Laurent Orseau, Petar Veličković, Anurag Murty Naredla, Joonkyung Lee, Adam Zsolt Wagner, Doina Precup

ICML 2023 Learning Instance-Specific Augmentations by Capturing Local Invariances Ning Miao, Tom Rainforth, Emile Mathieu, Yann Dubois, Yee Whye Teh, Adam Foster, Hyunjik Kim

ICLR 2023 Pre-Training via Denoising for Molecular Property Prediction Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter Battaglia, Razvan Pascanu, Jonathan Godwin

ICML 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

NeurIPSW 2022 Pre-Training via Denoising for Molecular Property Prediction Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter Battaglia, Razvan Pascanu, Jonathan Godwin

NeurIPSW 2022 When Does Re-Initialization Work? Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jorg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu

NeurIPS 2021 Group Equivariant Subsampling Jin Xu, Hyunjik Kim, Thomas Rainforth, Yee W. Teh

ICML 2021 LieTransformer: Equivariant Self-Attention for Lie Groups Michael J Hutchinson, Charline Le Lan, Sheheryar Zaidi, Emilien Dupont, Yee Whye Teh, Hyunjik Kim

ICML 2021 The Lipschitz Constant of Self-Attention Hyunjik Kim, George Papamakarios, Andriy Mnih

ICML 2020 MetaFun: Meta-Learning with Iterative Functional Updates Jin Xu, Jean-Francois Ton, Hyunjik Kim, Adam Kosiorek, Yee Whye Teh

ICLR 2019 Attentive Neural Processes Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, Ali Eslami, Dan Rosenbaum, Oriol Vinyals, Yee Whye Teh

ICML 2018 Disentangling by Factorising Hyunjik Kim, Andriy Mnih

AISTATS 2018 Scaling up the Automatic Statistician: Scalable Structure Discovery Using Gaussian Processes Hyunjik Kim, Yee Whye Teh

NeurIPS 2018 Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objects Adam Kosiorek, Hyunjik Kim, Yee Whye Teh, Ingmar Posner

AutoML 2016 Scalable Structure Discovery in Regression Using Gaussian Processes Hyunjik Kim, Yee Whye Teh