Lauro Langosco di Langosco

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 181 citations into it
• Safety, Robustness & Interpretability — 70 citations into it

Whom Lauro Langosco di Langosco trusts overall

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

1. Joseph B. Kruskal
2. Martín Arjovsky
3. John Schulman
4. Richard S. Sutton
5. Geoffrey E. Hinton
6. Diederik P. Kingma

Papers from Lauro Langosco di Langosco's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. Intriguing properties of neural networks
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Harms from Increasingly Agentic Algorithmic Systems (2023) — 259 citations
• Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback (2023) — 934 citations
• Objective Robustness in Deep Reinforcement Learning (2021) — 16 citations