Evangelos E. Papalexakis

Artificial Intelligence · 2012–2025

A researcher in the Science corpus: 14 papers; trusts 338 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 145 citations into it; #11,513 of 35,345 by trust here, #9,760 by citations
• Computational Mathematics — 101 citations into it; #201 of 612 by trust here, #118 by citations
• Computer Vision and Pattern Recognition — 71 citations into it; #21,426 of 21,575 by trust here, #17,757 by citations
• Signal Processing — 54 citations into it
• Representation & Self-Supervised Learning — 45 citations into it
• Information Systems — 31 citations into it
• Computational Theory and Mathematics — 30 citations into it
• Multimodal Learning — 28 citations into it; #1,207 of 1,211 by trust here, #1,119 by citations

Whom Evangelos E. Papalexakis trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Tamara G. Kolda
2. Evrim Acar
3. Rasmus Bro
4. Geoffrey E. Hinton
5. Brett W. Bader
6. Lars Grasedyck
7. Yoshua Bengio
8. Diederik P. Kingma
9. Kaiming He
10. Alex Krizhevsky

Who trusts Evangelos E. Papalexakis overall

1. Marinka Zitnik
2. N. Sidiropoulos
3. Jiajia Li
4. Andrzej S. Cichocki
5. Jean Kossaifi
6. Jimeng Sun
7. Joon Hee Choi
8. A. D. Almeida
9. Monica Agrawal
10. Joyce Ho

Papers from Evangelos E. Papalexakis's perspective

Ordered by how strongly the researchers Evangelos E. Papalexakis trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Webly Supervised Joint Embedding for Cross-Modal Image-Text Retrieval (2018) — 81 citations
• GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries (2012) — 304 citations
• GWTC-4.0: Population Properties of Merging Compact Binaries (2025) — 133 citations
• GW231123: A Binary Black Hole Merger with Total Mass 190–265 M⊙ (2025) — 139 citations
• GWTC-4.0: Updating the Gravitational-wave Transient Catalog with Observations from the First Part of the Fourth LIGO–Virgo–KAGRA Observing Run (2025) — 224 citations
• Observation of Gravitational Waves from the Coalescence of a 2.5–4.5 M ⊙ Compact Object and a Neutron Star (2024) — 186 citations
• Open Data from the Third Observing Run of LIGO, Virgo, KAGRA, and GEO (2023) — 273 citations
• All You Need Is Low (Rank): Defending Against Adversarial Attacks on Graphs (2020) — 399 citations
• SourceFinder: Finding Malware Source-Code from Publicly Available Repositories (2020) — 72 citations
• SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping (2018) — 589 citations
• COPA: Constrained PARAFAC2 for Sparse & Large Datasets (2018) — 47 citations
• Tensors for Data Mining and Data Fusion (2016) — 405 citations
• Tensor Decomposition for Signal Processing and Machine Learning (2016) — 1,589 citations
• FlexiFaCT: Scalable Flexible Factorization of Coupled Tensors on Hadoop (2014) — 122 citations