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Found 6 papers, 4 papers with code
Data Integration for Toxic Comment Classification: Making More Than 40 Datasets Easily Accessible in One Unified Format
With the rise of research on toxic comment classification, more and more annotated datasets have been released.
Virtual Reality for Understanding Artificial-Intelligence-driven Scientific Discovery with an Application in Quantum Optics
Thereby, we can manually discover new generalizations of AI-discoveries as well as new understanding in experimental quantum optics.
Learning Action Embeddings for Off-Policy Evaluation
Off-policy evaluation (OPE) methods allow us to compute the expected reward of a policy by using the logged data collected by a different policy.
Variational Boosted Soft Trees
Variational inference is often used to implement Bayesian neural networks, but is difficult to apply to GBMs, because the decision trees used as weak learners are non-differentiable.
More Than Words: Towards Better Quality Interpretations of Text Classifiers
The large size and complex decision mechanisms of state-of-the-art text classifiers make it difficult for humans to understand their predictions, leading to a potential lack of trust by the users.
Quantifying Interpretability and Trust in Machine Learning Systems
Our results complement existing qualitative work on trust and interpretability by quantifiable measures that can serve as objectives for further improving methods in this field of research.
