Guang Lin
16 papers · 2019–2026 · 9 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+8 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (34) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π
Keyword Champion
(4)
π
Grand Slam
π
Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
β‘
Prolific Year Β· Productive
π
Century Club Β· Bronze
π
Trend Setter
ποΈ
Keyword Collector
(74)
Top co-authors
Research topics
Machine Learning
(16)
Learning Types
(7)
Optimization & Theory
(7)
Artificial Intelligence
(6)
Bayesian & Probabilistic Β· Machine Learning
(5)
Core AI
(4)
Deep Learning
(3)
Core Methods
(3)
Mathematics & Optimization
(2)
Application Areas
(2)
Bayesian & Probabilistic Β· Artificial Intelligence
(2)
Learning Paradigms
(2)
Optimization
(2)
Computer Vision
(1)
Healthcare & Medicine
(1)
Keywords
markov chain monte carlo
(7)
replica exchange
(4)
langevin dynamics
(3)
posterior sampling
(2)
stochastic gradient descent
(2)
stochastic gradient langevin dynamics
(2)
neural network
(2)
parallel tempering
(2)
federated learning
(2)
adversarial robustness
(1)
feature extraction
(1)
domain adaptation
(1)
uncertainty quantification
(1)
mathematical reasoning
(1)
zero-shot learning
(1)
stochastic optimization
(1)
transfer learning
(1)
bayesian learning
(1)
adversarial training
(1)
convergence analysis
(1)
Papers
Exploring Non-Convex Discrete Energy Landscapes: An Efficient Langevin-Like Sampler with Replica Exchange
AAAI 2026
Hyperspectral Pansharpening via Diffusion Models with Iteratively Zero-Shot Guidance
CVPR 2025
LLM Reasoning Engine: Specialized Training for Enhanced Mathematical Reasoning
NAACL 2025
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo
AISTATS 2024
Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization
ICLR 2024
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
ICML 2024
Fair Supervised Learning with A Simple Random Sampler of Sensitive Attributes
AISTATS 2024
Federated X-armed Bandit
AAAI 2024
On Convergence of Federated Averaging Langevin Dynamics
UAI 2024
Non-reversible Parallel Tempering for Deep Posterior Approximation
AAAI 2023
Interacting Contour Stochastic Gradient Langevin Dynamics
ICLR 2022
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction
ICLR 2021
Multi-Branch Network for Cross-Subject EEG-based Emotion Recognition
ACML 2021
A Contour Stochastic Gradient Langevin Dynamics Algorithm for Simulations of Multi-modal Distributions
NeurIPS 2020
Non-convex Learning via Replica Exchange Stochastic Gradient MCMC
ICML 2020
An Adaptive Empirical Bayesian Method for Sparse Deep Learning
NeurIPS 2019