Giacomo Domeniconi
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 61 citations into it
- Information Systems — 32 citations into it
- Graph Learning — 29 citations into it
- Natural Language Processing — 25 citations into it
- Computer Vision and Pattern Recognition — 21 citations into it
- Software — 19 citations into it
- Representation & Self-Supervised Learning — 17 citations into it
- Statistical and Nonlinear Physics — 13 citations into it
Whom Giacomo Domeniconi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Radford M. Neal
- Michaël Defferrard
- Leland McInnes
- Trevor J. Hastie
- Thomas Kipf
- Geoffrey E. Hinton
- Xavier Bresson
- Mikhail Belkin
- Aldo Pareja
- Max Welling
Who trusts Giacomo Domeniconi overall
Papers from Giacomo Domeniconi's perspective
Ordered by how strongly the researchers Giacomo Domeniconi trusts endorse each paper. Same corpus, a different order for every researcher.
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial Forensics (2019) — 480 citations
- CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks (2021) — 391 citations
- Project CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks (2021) — 91 citations
- EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs (2019) — 1,524 citations