Jungtaek Kim
15 papers · 2019–2026 · 7 venues · across top CS/AI venues
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Achievements
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π Interdisciplinary Bridge Β· Silver π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π£ Hot Topic Early Bird πΊοΈ Taxonomy Completionist (35)
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Topic Evolution
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Triple Crown
ποΈ
Keyword Collector
(76)
π₯
Unstoppable Β· Bronze
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Renaissance Researcher
(7)
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Century Club Β· Bronze
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Research topics
Machine Learning
(12)
Optimization & Theory
(7)
Core Methods
(6)
Deep Learning
(5)
Artificial Intelligence
(4)
Mathematics & Optimization
(3)
Architectures
(3)
Bayesian & Probabilistic
(3)
Optimization
(3)
Core AI
(2)
Learning Types
(2)
Computer Science
(1)
Computer Vision
(1)
Natural Language Processing
(1)
Reinforcement Learning
(1)
Keywords
bayesian optimization
(4)
gaussian process
(3)
neural network
(2)
uncertainty quantification
(2)
few-shot learning
(1)
variational inference
(1)
representation learning
(1)
attention mechanism
(1)
semi-supervised learning
(1)
gaussian splatting
(1)
graph representation
(1)
model fusion
(1)
image processing
(1)
density ratio estimation
(1)
sequential optimization
(1)
stochastic process
(1)
hyperparameter optimization
(1)
image segmentation
(1)
multi-objective optimization
(1)
regret analysis
(1)
Papers
GP-4DGS: Probabilistic 4D Gaussian Splatting from Monocular Video via Variational Gaussian Processes
CVPR 2026
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning
ICML 2025
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data
ICML 2025
Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions
ICLR 2024
Model Fusion through Bayesian Optimization in Language Model Fine-Tuning
NeurIPS 2024
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
ICML 2024
Datasets and Benchmarks for Nanophotonic Structure and Parametric Design Simulations
NeurIPS 2023
Generative Neural Fields by Mixtures of Neural Implicit Functions
NeurIPS 2023
Combinatorial Bayesian optimization with random mapping functions to convex polytopes
UAI 2022
Learning to Assemble Geometric Shapes
IJCAI 2022
On Evaluation Metrics for Graph Generative Models
ICLR 2022
On Uncertainty Estimation by Tree-based Surrogate Models in Sequential Model-based Optimization
AISTATS 2022
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning
NeurIPS 2021
Bootstrapping neural processes
NeurIPS 2020
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
ICML 2019