Zeke Xie
21 papers · 2017–2026 · 6 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.
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🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (38) 🌍 Conference Polyglot · Silver 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint
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Prolific Year · Productive
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Unstoppable · Bronze
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Keyword Collector
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Research topics
Deep Learning
(17)
Machine Learning
(13)
Optimization & Theory · Machine Learning
(9)
Computer Vision
(8)
Models
(8)
Generation
(6)
Optimization & Theory · Deep Learning
(6)
Learning Types · Machine Learning
(4)
Learning Types · Deep Learning
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Architectures
(3)
Core Methods
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Techniques
(3)
Artificial Intelligence
(2)
Mathematics & Optimization
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Analysis
(2)
Keywords
diffusion model
(5)
stochastic gradient descent
(3)
image generation
(3)
flat minima
(2)
text-to-image generation
(2)
neural radiance field
(2)
video generation
(1)
double descent
(1)
stochastic gradient
(1)
disparity estimation
(1)
label propagation
(1)
feature selection
(1)
principal component analysis
(1)
event camera
(1)
reinforcement learning
(1)
preference optimization
(1)
knowledge distillation
(1)
text-to-image synthesis
(1)
image reconstruction
(1)
video synthesis
(1)
Papers
Accelerating Diffusion Model Training under Minimal Budgets: A Condensation-Based Perspective
CVPR 2026
CRAFT: Aligning Diffusion Models with Fine-Tuning Is Easier Than You Think
CVPR 2026
DIMOS: Disentangling Instance-level Moving Object Segmentation
CVPR 2026
FastLightGen: Fast and Light Video Generation with Fewer Steps and Parameters
CVPR 2026
Golden Noise for Diffusion Models: A Learning Framework
ICCV 2025
Investigating the Overlooked Hessian Structure: From CNNs to LLMs
ICML 2025
IV-mixed Sampler: Leveraging Image Diffusion Models for Enhanced Video Synthesis
ICLR 2025
Mono2Stereo: A Benchmark and Empirical Study for Stereo Conversion
CVPR 2025
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples
ICML 2025
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection
ICLR 2025
Neural Field Classifiers via Target Encoding and Classification Loss
ICLR 2024
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data
ICLR 2024
Dataset Pruning: Reducing Training Data by Examining Generalization Influence
ICLR 2023
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
NeurIPS 2023
On the Overlooked Structure of Stochastic Gradients
NeurIPS 2023
S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields
ICCV 2023
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
ICML 2022
Sparse Double Descent: Where Network Pruning Aggravates Overfitting
ICML 2022
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima
ICLR 2021
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization
ICML 2021
A Quantum-Inspired Ensemble Method and Quantum-Inspired Forest Regressors
ACML 2017