Mert Kilickaya

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 2 papers; trusts 235 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 65 citations into it; #22,798 of 35,345 by trust here, #18,186 by citations
• Computer Vision and Pattern Recognition — 64 citations into it; #14,138 of 21,575 by trust here, #12,172 by citations
• Meta & Continual Learning — 25 citations into it
• Representation & Self-Supervised Learning — 22 citations into it
• Natural Language Processing — 20 citations into it
• Evaluation & Benchmarks — 17 citations into it; #2,036 of 3,147 by trust here, #2,222 by citations
• Multimodal Learning — 10 citations into it

Whom Mert Kilickaya trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Ross B. Girshick
5. Yoshua Bengio
6. Yann LeCun
7. Diederik P. Kingma
8. Ilya Sutskever
9. Xinlei Chen
10. Oriol Vinyals

Who trusts Mert Kilickaya overall

1. Asli Celikyilmaz
2. Elizabeth Clark
3. Matteo Stefanini
4. Xiangyang Li
5. Ananya B. Sai
6. Julian Chow
7. Jekaterina Novikova
8. Marcella Cornia
9. Shuqiang Jiang
10. Ehud Reiter

Papers from Mert Kilickaya's perspective

Ordered by how strongly the researchers Mert Kilickaya 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Re-evaluating Automatic Metrics for Image Captioning (2016) — 194 citations
• Towards Label-Efficient Incremental Learning: A Survey (2023) — 5 citations