Justin M Solomon
12 papers · 2017–2023 · 2 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (31) π Academic Marathon Β· Sprint π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Topic Evolution
ποΈ
Keyword Collector
(59)
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Renaissance Researcher
(5)
π₯
Unstoppable Β· Bronze
β
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Venues
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Research topics
Machine Learning
(10)
Mathematics & Optimization
(8)
Optimization
(7)
Core Methods
(5)
Mathematics
(5)
Optimization & Theory
(5)
Deep Learning
(4)
Computer Vision
(3)
Architectures
(3)
Learning Types
(3)
Artificial Intelligence
(2)
Analysis
(2)
Models
(2)
Data Science & Analytics
(1)
Natural Language Processing
(1)
Keywords
optimal transport
(7)
wasserstein distance
(2)
wasserstein barycenter
(2)
image generation
(2)
fokker-planck equation
(2)
wasserstein gradient flow
(2)
bayesian inference
(2)
input convex neural network
(2)
probability distribution
(2)
self-supervised learning
(2)
stochastic gradient descent
(2)
mean estimation
(1)
convex optimization
(1)
point cloud
(1)
topic modeling
(1)
knowledge distillation
(1)
manifold learning
(1)
message passing
(1)
outlier detection
(1)
document representation
(1)
Papers
Self-Consistent Velocity Matching of Probability Flows
NeurIPS 2023
Log-Euclidean Signatures for Intrinsic Distances Between Unaligned Datasets
ICML 2022
Do Neural Optimal Transport Solvers Work? A Continuous Wasserstein-2 Benchmark
NeurIPS 2021
Large-Scale Wasserstein Gradient Flows
NeurIPS 2021
MarioNette: Self-Supervised Sprite Learning
NeurIPS 2021
Object DGCNN: 3D Object Detection using Dynamic Graphs
NeurIPS 2021
Outlier-Robust Optimal Transport
ICML 2021
Continuous Regularized Wasserstein Barycenters
NeurIPS 2020
Alleviating Label Switching with Optimal Transport
NeurIPS 2019
Hierarchical Optimal Transport for Document Representation
NeurIPS 2019
PRNet: Self-Supervised Learning for Partial-to-Partial Registration
NeurIPS 2019
Parallel Streaming Wasserstein Barycenters
NeurIPS 2017