Adam Baker

Artificial Intelligence · with Johri · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it
• Probabilistic & Bayesian Methods — 27 citations into it
• Management Science and Operations Research — 11 citations into it
• Causal Inference & Discovery — 9 citations into it
• Statistics and Probability — 5 citations into it

Whom Adam Baker trusts overall

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

1. Daphne Koller
2. Quaid D. Morris
3. Radford M. Neal
4. Yura N. Perov

Papers from Adam Baker's perspective

Ordered by how strongly the researchers Adam Baker 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. Dropout: a simple way to prevent neural networks from overfitting
3. ImageNet classification with deep convolutional neural networks
4. Playing Atari with Deep Reinforcement Learning (arXiv.org)
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Gradient-based learning applied to document recognition
7. Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
8. Long Short-Term Memory
9. Prioritized Experience Replay
10. MADE: Masked Autoencoder for Distribution Estimation

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 comparative study of artificial intelligence and human doctors for the purpose of triage and diagnosis (2018) — 96 citations
• A Universal Marginalizer for Amortized Inference in Generative Models (2017) — 31 citations