| Transparency, Governance and Regulation of Algorithmic Tools Deployed in the Criminal Justice System: a UK Case Study. | 0 | 0.34 | 2022 |
| Dimensions of Diversity in Human Perceptions of Algorithmic Fairness. | 0 | 0.34 | 2022 |
| How transparency modulates trust in artificial intelligence | 0 | 0.34 | 2022 |
| CrossWalk: Fairness-Enhanced Node Representation Learning. | 0 | 0.34 | 2022 |
| Structural Causal 3D Reconstruction. | 0 | 0.34 | 2022 |
| Eliciting and Learning with Soft Labels from Every Annotator. | 0 | 0.34 | 2022 |
| On the Utility of Prediction Sets in Human-AI Teams | 0 | 0.34 | 2022 |
| Racial Disparities in the Enforcement of Marijuana Violations in the US. | 0 | 0.34 | 2022 |
| Diverse, Global and Amortised Counterfactual Explanations for Uncertainty Estimates. | 0 | 0.34 | 2022 |
| On the Utility of Prediction Sets in Human-AI Teams. | 0 | 0.34 | 2022 |
| From block-Toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked Transformers. | 0 | 0.34 | 2022 |
| Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence (vol 3, pg 1081, 2021) | 0 | 0.34 | 2022 |
| Measuring Representational Robustness of Neural Networks Through Shared Invariances. | 0 | 0.34 | 2022 |
| Towards Principled Disentanglement for Domain Generalization | 0 | 0.34 | 2022 |
| Multi-disciplinary fairness considerations in machine learning for clinical trials. | 0 | 0.34 | 2022 |
| Robust Learning from Observation with Model Misspecification. | 0 | 0.34 | 2022 |
| On the Fairness of Causal Algorithmic Recourse. | 0 | 0.34 | 2022 |
| Hybrid Random Features | 0 | 0.34 | 2022 |
| Rethinking Attention with Performers | 0 | 0.34 | 2021 |
| Getting a CLUE: A Method for Explaining Uncertainty Estimates | 0 | 0.34 | 2021 |
| Advancing COVID-19 diagnosis with privacy-preserving collaboration in artificial intelligence | 0 | 0.34 | 2021 |
| Sub-Linear Memory: How to Make Performers SLiM. | 0 | 0.34 | 2021 |
| Cwy Parametrization: A Solution For Parallelized Optimization Of Orthogonal And Stiefel Matrices | 0 | 0.34 | 2021 |
| An Algorithmic Framework for Positive Action. | 0 | 0.34 | 2021 |
| Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty | 0 | 0.34 | 2021 |
| Debiasing A First-Order Heuristic For Approximate Bi-Level Optimization | 0 | 0.34 | 2021 |
| Adversarial Graph Embeddings for Fair Influence Maximization over Social Networks | 0 | 0.34 | 2020 |
| Stochastic Flows and Geometric Optimization on the Orthogonal Group | 0 | 0.34 | 2020 |
| Evaluating and Aggregating Feature-based Model Explanations | 0 | 0.34 | 2020 |
| Now You See Me (CME): Concept-based Model Extraction | 0 | 0.34 | 2020 |
| Human-Centered Approaches to Fair and Responsible AI | 0 | 0.34 | 2020 |
| Fair Enough - Improving Fairness in Budget-Constrained Decision Making Using Confidence Thresholds. | 0 | 0.34 | 2020 |
| Ode to an ODE. | 0 | 0.34 | 2020 |
| Leveraging Data Science to Combat COVID-19: A Comprehensive Review | 6 | 0.47 | 2020 |
| Train and Test Tightness of LP Relaxations in Structured Prediction. | 0 | 0.34 | 2019 |
| The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. | 1 | 0.36 | 2019 |
| Leader Stochastic Gradient Descent for Distributed Training of Deep Learning Models. | 0 | 0.34 | 2019 |
| One-Network Adversarial Fairness | 0 | 0.34 | 2019 |
| Unifying Orthogonal Monte Carlo Methods | 2 | 0.35 | 2019 |
| Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems - Directions and Differences. | 0 | 0.34 | 2019 |
| TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning | 0 | 0.34 | 2019 |
| Motivations and Risks of Machine Ethics | 1 | 0.39 | 2019 |
| Structured Evolution with Compact Architectures for Scalable Policy Optimization. | 9 | 0.55 | 2018 |
| Blind Justice: Fairness with Encrypted Sensitive Attributes. | 4 | 0.50 | 2018 |
| Geometrically Coupled Monte Carlo Sampling. | 2 | 0.38 | 2018 |
| Discovering Interpretable Representations for Both Deep Generative and Discriminative Models. | 1 | 0.36 | 2018 |
| Beyond Distributive Fairness in Algorithmic Decision Making: Feature Selection for Procedurally Fair Learning. | 10 | 0.56 | 2018 |
| Purple Feed: Identifying High Consensus News Posts On Social Media | 1 | 0.35 | 2018 |
| Bucket renormalization for approximate inference | 1 | 0.35 | 2018 |
| A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices. | 15 | 0.60 | 2018 |
