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Found 7 papers, 3 papers with code
A Simple Baseline for Predicting Events with Auto-Regressive Tabular Transformers
Moreover, these approaches often assume specific use-cases, for example that we know the labels of all historic events or that we only predict a pre-specified label and not the data's features themselves.
Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning
Vision transformers have established a precedent of patchifying images into uniformly-sized chunks before processing.
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence
By perturbing the input variables in rank order of importance, the goal is to assess the sensitivity of the model's performance.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
Counterfactual Explanations via Latent Space Projection and Interpolation
Counterfactual explanations represent the minimal change to a data sample that alters its predicted classification, typically from an unfavorable initial class to a desired target class.
Dynamic Customer Embeddings for Financial Service Applications
As financial services (FS) companies have experienced drastic technology driven changes, the availability of new data streams provides the opportunity for more comprehensive customer understanding.
Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations
In the environment of fair lending laws and the General Data Protection Regulation (GDPR), the ability to explain a model's prediction is of paramount importance.
Visual Natural Language Query Auto-Completion for Estimating Instance Probabilities
Given the complete query, we fine tune a BERT embedding for estimating probabilities of a broad set of instances.
