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← Authors

Eran Treister

16 papers · 2014–2025 · 6 conferences · across top CS/AI conferences

Achievements

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+8 more ↓ πŸƒ Academic Marathon (11) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (9)
🐝 Cross-Pollinator (9) πŸ—ΊοΈ Taxonomy Completionist (24) πŸ† Grand Slam 🧬 Topic Evolution πŸ”₯ Unstoppable (7) πŸ—ƒοΈ Keyword Collector (58) πŸ’Ž Century Club (16) ⚑ Prolific Year (5)

Conferences

ICML (6) NIPS (5) AISTATS (2) AAAI (1) ECCV (1) ICLR (1)

Top co-authors

Moshe Eliasof (8) Eldad Haber (5) Maor Ashkenazi (3) Shahaf E. Finder (2) Lars Ruthotto (2) Oren Freifeld (2) Elad Richardson (1) Ron Shapira Weber (1) Yair Zohav (1) Shir Levi (1)

Keywords

graph neural network (6) node classification (4) neural network (2) semantic segmentation (2) convolutional neural network (2) graph classification (2) precision matrix (2) graph convolutional network (2) temporal dynamics (1) hierarchical representation (1) feature extraction (1) message passing (1) l1 regularization (1) random walk (1) representation learning (1) covariance estimation (1) gaussian markov random field (1) wavelet transform (1) graph laplacian (1) block coordinate descent (1)

Papers

Improving the Effective Receptive Field of Message-Passing Neural Networks ICML 2025 Disparate Conditional Prediction in Multiclass Classifiers ICML 2025 Wavelet Convolutions for Large Receptive Fields ECCV 2024 Towards Croppable Implicit Neural Representations NIPS 2024 Feature Transportation Improves Graph Neural Networks AAAI 2024 Efficient Graph Laplacian Estimation by Proximal Newton AISTATS 2024 On The Temporal Domain of Differential Equation Inspired Graph Neural Networks AISTATS 2024 Improving Graph Neural Networks with Learnable Propagation Operators ICML 2023 NeRN: Learning Neural Representations for Neural Networks ICLR 2023 Graph Positional Encoding via Random Feature Propagation ICML 2023 Wavelet Feature Maps Compression for Image-to-Image CNNs NIPS 2022 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 IMEXnet A Forward Stable Deep Neural Network ICML 2019 A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance Estimation NIPS 2014