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Eran Treister

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

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (26) 🌍 Conference Polyglot Β· Silver πŸƒ Academic Marathon Β· Half πŸŒ‰ Interdisciplinary Bridge Β· Bronze 🐣 Hot Topic Early Bird
🧬 Topic Evolution πŸ† Grand Slam ⚑ Prolific Year Β· Productive πŸ”₯ Unstoppable Β· Bronze πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (76)

Venues

ICML (6) NeurIPS (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)

Research topics

Deep Learning (12) Architectures (11) Machine Learning (8) Core Methods (4) Computer Vision (3) Optimization & Theory (3) Mathematics & Optimization (2) Analysis (2) Application Areas (2) Mathematics (2) Optimization (2) Processing (2) Techniques (2) Artificial Intelligence (1) Core AI (1)

Keywords

graph neural network (6) node classification (4) convolutional neural network (3) neural network (2) precision matrix (2) semantic segmentation (2) graph convolutional network (2) graph classification (2) temporal dynamics (1) wavelet transform (1) feature extraction (1) covariance estimation (1) hierarchical representation (1) message passing (1) representation learning (1) depth estimation (1) spectral analysis (1) fairness (1) graph laplacian (1) sparse inverse covariance (1)

Papers

Disparate Conditional Prediction in Multiclass Classifiers ICML 2025 Improving the Effective Receptive Field of Message-Passing Neural Networks ICML 2025 Efficient Graph Laplacian Estimation by Proximal Newton AISTATS 2024 Feature Transportation Improves Graph Neural Networks AAAI 2024 On The Temporal Domain of Differential Equation Inspired Graph Neural Networks AISTATS 2024 Towards Croppable Implicit Neural Representations NeurIPS 2024 Wavelet Convolutions for Large Receptive Fields ECCV 2024 Graph Positional Encoding via Random Feature Propagation ICML 2023 Improving Graph Neural Networks with Learnable Propagation Operators ICML 2023 NeRN: Learning Neural Representations for Neural Networks ICLR 2023 pathGCN: Learning General Graph Spatial Operators from Paths ICML 2022 Wavelet Feature Maps Compression for Image-to-Image CNNs NeurIPS 2022 PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations NeurIPS 2021 DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling NeurIPS 2020 IMEXnet A Forward Stable Deep Neural Network ICML 2019 A Block-Coordinate Descent Approach for Large-scale Sparse Inverse Covariance Estimation NeurIPS 2014