Suchi Saria

Artificial Intelligence · 2013–2022

A researcher in the Science corpus: 22 papers; trusts 182 researchers and is trusted by 48 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 127 citations into it; #7,072 of 35,345 by trust here, #6,569 by citations
• Statistics and Probability — 119 citations into it; #4,816 of 12,932 by trust here, #4,517 by citations
• Causal Inference & Discovery — 44 citations into it; #106 of 364 by trust here, #127 by citations
• Epidemiology — 40 citations into it; #222 of 2,148 by trust here, #759 by citations
• Probabilistic & Bayesian Methods — 31 citations into it; #1,328 of 1,525 by trust here, #1,244 by citations
• Management Science and Operations Research — 29 citations into it; #9,247 of 11,946 by trust here, #8,062 by citations
• Medical & Health AI — 25 citations into it; #21 of 239 by trust here, #56 by citations
• Reinforcement Learning — 24 citations into it

Whom Suchi Saria trusts overall

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

1. Donald B. Rubin
2. James M. Robins
3. Mohammed Saeed
4. Judea Pearl
5. Thorsten Joachims
6. Peter F. Schulam
7. Elias Bareinboim
8. Bernhard Schölkopf
9. Mohammed Saeed
10. J. Lok

Who trusts Suchi Saria overall

1. Peter F. Schulam
2. Ioana Bica
3. Ahmed M. Alaa
4. Adarsh Subbaswamy
5. Hossein Soleimani
6. Bryan Lim
7. Mihaela van der Schaar
8. Bernhard Schölkopf
9. Ali Malik
10. Yanbo Xu

Papers from Suchi Saria's perspective

Ordered by how strongly the researchers Suchi Saria 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Counterfactual Normalization: Proactively Addressing Dataset Shift and Improving Reliability Using Causal Mechanisms (2018) — 27 citations
• A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure (2015) — 104 citations
• Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction (2017) — 60 citations
• The Clinician and Dataset Shift in Artificial Intelligence (2021) — 593 citations
• Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery (2015) — 116 citations
• Learning (predictive) risk scores in the presence of censoring due to interventions (2015) — 39 citations
• A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves (2016) — 42 citations
• Learning Treatment-Response Models from Multivariate Longitudinal Data (2017) — 21 citations
• Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist (2020) — 485 citations
• What-If Reasoning with Counterfactual Gaussian Processes (2017) — 8 citations
• Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI (2022) — 554 citations
• Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI (2022) — 405 citations
• Do no harm: a roadmap for responsible machine learning for health care (2019) — 925 citations
• Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport (2018) — 163 citations
• Individualized sepsis treatment using reinforcement learning (2018) — 67 citations
• Reliable Decision Support using Counterfactual Models (2017) — 227 citations
• A Bayesian Nonparametic Approach for Estimating Individualized Treatment-Response Curves (2016)
• Using Causal Inference to Estimate What-if Outcomes for Targeting Treatments (2016)
• A targeted real-time early warning score (TREWScore) for septic shock (2015) — 588 citations
• A Probabilistic Graphical Model for Individualizing Prognosis in Chronic, Complex Diseases (2015)