Il-chul Moon
31 papers · 2016–2025 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (57) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Dynamic Duo
(13)
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Keyword Champion
(2)
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Grand Slam
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Conference Pioneer
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Renaissance Researcher
(5)
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Keyword Collector
(145)
Top co-authors
Research topics
Machine Learning
(24)
Deep Learning
(20)
Learning Types Β· Machine Learning
(13)
Application Areas
(10)
Learning Types Β· Deep Learning
(10)
Core Methods
(9)
Optimization & Theory
(9)
Architectures
(7)
Models
(7)
Artificial Intelligence
(5)
Core AI
(5)
Computer Vision
(4)
Reinforcement Learning
(2)
Generation
(2)
Methods
(2)
Keywords
diffusion model
(6)
representation learning
(4)
generative model
(4)
image generation
(3)
latent space
(2)
dataset distillation
(2)
score-based model
(2)
active learning
(2)
acquisition function
(2)
loss landscape
(2)
attention mechanism
(2)
adversarial learning
(2)
multi-agent reinforcement learning
(2)
sequential recommendation
(2)
knowledge distillation
(2)
label noise
(2)
data augmentation
(2)
neural network optimization
(2)
recurrent neural network
(2)
synthetic dataset
(2)
Papers
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
ICLR 2025
Distilling Dataset into Neural Field
ICLR 2025
Trajectory-Class-Aware Multi-Agent Reinforcement Learning
ICLR 2025
Diffusion Rejection Sampling
ICML 2024
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
ICLR 2024
Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning
ICLR 2024
Label-Noise Robust Diffusion Models
ICLR 2024
LAGMA: LAtent Goal-guided Multi-Agent Reinforcement Learning
ICML 2024
Make Prompts Adaptable: Bayesian Modeling for Vision-Language Prompt Learning with Data-Dependent Prior
AAAI 2024
Reward-based Input Construction for Cross-document Relation Extraction
ACL 2024
Training Unbiased Diffusion Models From Biased Dataset
ICLR 2024
Unknown Domain Inconsistency Minimization for Domain Generalization
ICLR 2024
Frequency Domain-Based Dataset Distillation
NeurIPS 2023
Loss-Curvature Matching for Dataset Selection and Condensation
AISTATS 2023
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
ICML 2023
SAAL: Sharpness-Aware Active Learning
ICML 2023
From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model
ICML 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Model
NeurIPS 2022
Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation
ICML 2022
Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation
NeurIPS 2022
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder
AAAI 2021
Implicit Kernel Attention
AAAI 2021
LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning
NeurIPS 2021
Refine Myself by Teaching Myself: Feature Refinement via Self-Knowledge Distillation
CVPR 2021
Bivariate Beta-LSTM
AAAI 2020
Hierarchically Clustered Representation Learning
AAAI 2020
Neutralizing Gender Bias in Word Embeddings with Latent Disentanglement and Counterfactual Generation
EMNLP 2020
Sequential Recommendation with Relation-Aware Kernelized Self-Attention
AAAI 2020
Adversarial Dropout for Recurrent Neural Networks
AAAI 2019
Hierarchical Context Enabled Recurrent Neural Network for Recommendation
AAAI 2019
Bayesian Nonparametric Collaborative Topic Poisson Factorization for Electronic Health Records-Based Phenotyping
IJCAI 2016