Moshe Eliasof
18 papers · 2020–2026 · 6 conferences · across top CS/AI conferences
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NIPS (5)
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Keywords
graph neural network
(11)
node classification
(4)
message passing
(3)
graph classification
(2)
representation learning
(2)
graph convolutional network
(2)
diffeomorphic transformation
(2)
image generation
(1)
feature learning
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prior learning
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flow matching
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parameter efficient
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hierarchical representation
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batch normalization
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video prediction
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multi-task learning
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spectral analysis
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likelihood maximization
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dynamical system
(1)
singular value decomposition
(1)
Papers
Graph Flow Matching: Enhancing Image Generation with Neighbor-Aware Flow Fields
AAAI 2026
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations
CVPR 2025
Learning Regularization for Graph Inverse Problems
AAAI 2025
On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
AAAI 2025
Estimation of single-cell and tissue perturbation effect in spatial transcriptomics via Spatial Causal Disentanglement
ICLR 2025
Graph Adaptive Autoregressive Moving Average Models
ICML 2025
Improving the Effective Receptive Field of Message-Passing Neural Networks
ICML 2025
DiGRAF: Diffeomorphic Graph-Adaptive Activation Function
NIPS 2024
On The Temporal Domain of Differential Equation Inspired Graph Neural Networks
AISTATS 2024
Feature Transportation Improves Graph Neural Networks
AAAI 2024
Efficient Subgraph GNNs by Learning Effective Selection Policies
ICLR 2024
GRANOLA: Adaptive Normalization for Graph Neural Networks
NIPS 2024
Advection Augmented Convolutional Neural Networks
NIPS 2024
Improving Graph Neural Networks with Learnable Propagation Operators
ICML 2023
Graph Positional Encoding via Random Feature Propagation
ICML 2023
pathGCN: Learning General Graph Spatial Operators from Paths
ICML 2022
PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations
NIPS 2021
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling
NIPS 2020