Aaron Lou
12 papers · 2020–2024 · 4 conferences · across top CS/AI conferences
Achievements
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π Cross-Pollinator (11) π Interdisciplinary Bridge π§ Keyword Pioneer π Conference Polyglot (4) π Renaissance Researcher (5)
π
Interdisciplinary Bridge
π§
Keyword Pioneer
π
Triple Crown
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(56)
π
Century Club
(12)
Conferences
NIPS (6)
ICML (4)
CVPR (1)
ICLR (1)
Top co-authors
Keywords
diffusion model
(3)
manifold learning
(3)
generative model
(2)
representation learning
(2)
geometric deep learning
(2)
hyperbolic space
(2)
riemannian manifold
(2)
batch normalization
(1)
direct preference optimization
(1)
image generation
(1)
model alignment
(1)
intrinsic dimension
(1)
generalization error
(1)
protein design
(1)
reinforcement learning from human feedback
(1)
topological data analysis
(1)
persistent homology
(1)
score matching
(1)
geometric prior
(1)
text-to-image generation
(1)
Papers
Equivariant Graph Neural Operator for Modeling 3D Dynamics
ICML 2024
Geometric Trajectory Diffusion Models
NIPS 2024
Diffusion Model Alignment Using Direct Preference Optimization
CVPR 2024
Denoising Diffusion Bridge Models
ICLR 2024
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
ICML 2024
Riemannian Residual Neural Networks
NIPS 2023
Reflected Diffusion Models
ICML 2023
Scaling Riemannian Diffusion Models
NIPS 2023
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks
NIPS 2021
Equivariant Manifold Flows
NIPS 2021
Differentiating through the FrΓ©chet Mean
ICML 2020
Neural Manifold Ordinary Differential Equations
NIPS 2020