Nathanael Perraudin
8 papers · 2019–2024 · 4 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (16) 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Silver
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Triple Crown
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Grand Slam
Venues
Top co-authors
Research topics
Machine Learning
(7)
Deep Learning
(6)
Architectures
(4)
Core Methods
(4)
Optimization & Theory · Machine Learning
(4)
Artificial Intelligence
(3)
Core AI
(3)
Learning Types · Machine Learning
(3)
Models
(3)
Computer Vision
(1)
Mathematics & Optimization
(1)
Generation
(1)
Learning Types · Deep Learning
(1)
Mathematics
(1)
Optimization & Theory · Deep Learning
(1)
Keywords
generative adversarial network
(3)
graph generation
(2)
graph neural network
(2)
graph learning
(1)
explainable ai
(1)
feature importance
(1)
model interpretability
(1)
graph embedding
(1)
saliency map
(1)
n-body problems
(1)
spectral analysis
(1)
approximate nearest neighbor
(1)
convolutional neural network
(1)
duality gap
(1)
state-of-the-art performance
(1)
denoising diffusion
(1)
evaluation metric
(1)
short-time fourier transform
(1)
physics simulation
(1)
particle simulation
(1)
Papers
Efficient and Scalable Graph Generation through Iterative Local Expansion
ICLR 2024
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators
ICML 2022
What You See is What You Classify: Black Box Attributions
NeurIPS 2022
Scalable Graph Networks for Particle Simulations
AAAI 2021
DeepSphere: a graph-based spherical CNN
ICLR 2020
A Domain Agnostic Measure for Monitoring and Evaluating GANs
NeurIPS 2019
Adversarial Generation of Time-Frequency Features with application in audio synthesis
ICML 2019
Large Scale Graph Learning From Smooth Signals
ICLR 2019