← Authors

Saehoon Kim

15 papers · 2015–2024 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (9) 🐝 Cross-Pollinator (4) 🌈 Renaissance Researcher (8) πŸ—ΊοΈ Taxonomy Completionist (31) 🧬 Topic Evolution πŸ† Keyword Champion πŸ“ˆ Trend Setter πŸ’Ž Century Club (15) ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (61)

Conferences

NIPS (5) CVPR (4) ICLR (4) AAAI (1) COLING (1)

Top co-authors

Sung Ju Hwang (6) Eunho Yang (6) Doyup Lee (5) Chiheon Kim (4) Juho Lee (4) Minsu Cho (3) Hae Beom Lee (3) Kwang Joon Kim (2) Wook-Shin Han (2) Bohyung Han (2)

Keywords

variational inference (3) image generation (3) residual quantization (2) electronic health record (2) variational autoencoder (2) vector quantization (2) autoregressive model (2) similarity search (1) embedding space (1) zero-shot learning (1) text-to-image generation (1) flow matching (1) gaussian process (1) time series (1) instance pattern composers (1) implicit neural representation (1) conditional generation (1) adaptive dropout (1) locality-sensitive hashing (1) attention mechanism (1)

Papers

Simulation-Free Training of Neural ODEs on Paired Data NIPS 2024
Generalizable Implicit Neural Representations via Instance Pattern Composers CVPR 2023
Variational Distribution Learning for Unsupervised Text-to-Image Generation CVPR 2023
Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss COLING 2022
Autoregressive Image Generation Using Residual Quantization CVPR 2022
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity ICLR 2022
Draft-and-Revise: Effective Image Generation with Contextual RQ-Transformer NIPS 2022
Locally Hierarchical Auto-Regressive Modeling for Image Generation NIPS 2022
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution Tasks ICLR 2020
Scalable and Order-robust Continual Learning with Additive Parameter Decomposition ICLR 2020
Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare AAAI 2020
LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING ICLR 2019
Uncertainty-Aware Attention for Reliable Interpretation and Prediction NIPS 2018
DropMax: Adaptive Variational Softmax NIPS 2018
Bilinear Random Projections for Locality-Sensitive Binary Codes CVPR 2015