Giung Nam
11 papers · 2021–2025 · 3 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Bronze πΊοΈ Taxonomy Completionist (23) π Keyword Champion (3) π€ Dynamic Duo (11) ποΈ Keyword Collector (53)
π₯
Unstoppable Β· Bronze
π
Trend Setter
π
Century Club Β· Bronze
Venues
Top co-authors
Research topics
Machine Learning
(10)
Deep Learning
(8)
Application Areas
(6)
Optimization & Theory Β· Machine Learning
(5)
Artificial Intelligence
(4)
Bayesian & Probabilistic
(3)
Architectures
(2)
Core Methods
(2)
Learning Paradigms
(2)
Learning Types Β· Deep Learning
(2)
Learning Types Β· Machine Learning
(2)
Models
(2)
Techniques
(2)
Optimization & Theory Β· Deep Learning
(1)
Keywords
neural network ensemble
(3)
deep ensemble
(2)
uncertainty estimation
(2)
weight averaging
(2)
posterior sampling
(2)
knowledge distillation
(2)
neural network
(2)
distribution shift
(2)
image classification
(2)
probabilistic modeling
(1)
model merging
(1)
zero-shot learning
(1)
flow matching
(1)
representation learning
(1)
model calibration
(1)
ensemble learning
(1)
bayesian model averaging
(1)
gaussian process
(1)
transfer learning
(1)
nonparametric learning
(1)
Papers
Ensemble Distribution Distillation via Flow Matching
ICML 2025
Parameter Expanded Stochastic Gradient Markov Chain Monte Carlo
ICLR 2025
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
ICLR 2024
Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems
NeurIPS 2024
Lipsum-FT: Robust Fine-Tuning of Zero-Shot Models Using Random Text Guidance
ICLR 2024
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
ICLR 2024
Decoupled Training for Long-Tailed Classification With Stochastic Representations
ICLR 2023
Martingale Posterior Neural Processes
ICLR 2023
Traversing Between Modes in Function Space for Fast Ensembling
ICML 2023
Improving Ensemble Distillation With Weight Averaging and Diversifying Perturbation
ICML 2022
Diversity Matters When Learning From Ensembles
NeurIPS 2021