Jernej Kos
Artificial Intelligence · 2017–2020
A researcher in the Science corpus: 8 papers; trusts 158 researchers and is trusted by 38 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 199 citations into it; #7,283 of 35,345 by trust here, #3,598 by citations
- Safety, Robustness & Interpretability — 63 citations into it; #423 of 2,251 by trust here, #238 by citations
- Computer Vision and Pattern Recognition — 53 citations into it; #13,951 of 21,575 by trust here, #8,952 by citations
- Information Systems — 40 citations into it; #3,938 of 8,771 by trust here, #529 by citations
- Natural Language Processing — 31 citations into it
- Reinforcement Learning — 31 citations into it
- Optimization & Training — 30 citations into it
- Signal Processing — 24 citations into it
Whom Jernej Kos trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Ian J. Goodfellow
- Geoffrey E. Hinton
- Yoshua Bengio
- Yann LeCun
- Christian Szegedy
- Ilya Sutskever
- Alex Krizhevsky
- Jimmy Ba
- Alex Graves
Who trusts Jernej Kos overall
- Nicholas Carlini
- Vikash Sehwag
- Xiaoyong Yuan
- Naveed Akhtar
- Mathias Lécuyer
- Anay Pattanaik
- Ivan Evtimov
- Kevin Eykholt
- Arjun Nitin Bhagoji
- Matthias Hein
Papers from Jernej Kos's perspective
Ordered by how strongly the researchers Jernej Kos trusts endorse each paper. Same corpus, a different order for every researcher.
- 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
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks (2018) — 1,449 citations
- Adversarial Examples for Generative Models (2017) — 289 citations
- Assessing Generalization in Deep Reinforcement Learning (2018) — 279 citations
- Delving into adversarial attacks on deep policies (2017) — 258 citations
- Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contracts (2018) — 428 citations
- The Ekiden Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contracts (2020) — 8 citations
- Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contract Execution (2018) — 110 citations
- The Secret Sharer: Measuring Unintended Neural Network Memorization & Extracting Secrets (2018) — 200 citations