Kostis Gourgoulias

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it
• Probabilistic & Bayesian Methods — 24 citations into it
• Management Science and Operations Research — 10 citations into it
• Causal Inference & Discovery — 9 citations into it
• Statistics and Probability — 5 citations into it

Whom Kostis Gourgoulias trusts overall

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

1. Quaid D. Morris
2. Yura N. Perov
3. Radford M. Neal
4. Diederik P. Kingma
5. Shixiang Shane Gu
6. Frank D. Wood
7. Brooks Paige
8. Thomas S. Richardson
9. Mingxiang Li
10. Geoffrey E. Hinton

Papers from Kostis Gourgoulias's perspective

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

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Dropout: a simple way to prevent neural networks from overfitting
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Playing Atari with Deep Reinforcement Learning (arXiv.org)
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• Learning medical triage from clinicians using Deep Q-Learning (2020) — 4 citations
• MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming (2019) — 19 citations
• A Universal Marginalizer for Amortized Inference in Generative Models (2017) — 31 citations