Aaron Lou
12 papers · 2020–2024 · 4 venues · across top CS/AI venues
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Achievements
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🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (26) 🏆 Keyword Champion
👑
Triple Crown
🗃️
Keyword Collector
(69)
💎
Century Club · Bronze
⚡
Prolific Year · Productive
Venues
Top co-authors
Research topics
Machine Learning
(10)
Deep Learning
(9)
Models
(7)
Core Methods
(5)
Optimization & Theory
(5)
Artificial Intelligence
(4)
Core AI
(4)
Computer Vision
(3)
Generation
(3)
Learning Types
(3)
Architectures
(2)
Techniques
(2)
Data Science & Analytics
(1)
Mathematics & Optimization
(1)
Application Areas
(1)
Keywords
diffusion model
(5)
generative model
(3)
manifold learning
(3)
geometric deep learning
(2)
representation learning
(2)
score matching
(2)
riemannian manifold
(2)
hyperbolic space
(2)
se(3) equivariance
(2)
direct preference optimization
(1)
image-to-image translation
(1)
flow matching
(1)
topological data analysis
(1)
reinforcement learning from human feedback
(1)
optimal transport
(1)
image generation
(1)
geometric prior
(1)
text-to-image generation
(1)
protein design
(1)
generalization error
(1)
Papers
Denoising Diffusion Bridge Models
ICLR 2024
Diffusion Model Alignment Using Direct Preference Optimization
CVPR 2024
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
ICML 2024
Equivariant Graph Neural Operator for Modeling 3D Dynamics
ICML 2024
Geometric Trajectory Diffusion Models
NeurIPS 2024
Reflected Diffusion Models
ICML 2023
Riemannian Residual Neural Networks
NeurIPS 2023
Scaling Riemannian Diffusion Models
NeurIPS 2023
Equivariant Manifold Flows
NeurIPS 2021
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks
NeurIPS 2021
Differentiating through the Fréchet Mean
ICML 2020
Neural Manifold Ordinary Differential Equations
NeurIPS 2020