8 citations · 8 across the 3 of their papers we have counts for
3 papers
Hybrid Data can Enhance the Utility of Synthetic Data for Training Anti-Money Laundering Models
Rachel Chung, Pratyush Nidhi Sharma, Mikko Siponen +2
Money laundering is a critical global issue for financial institutions. Automated Anti-money laundering (AML) models, like Graph Neural Networks (GNN), can be trained to identify i…
FLUX.1 Kontext: Flow Matching for In-Context Image Generation and Editing in Latent Space
Black Forest Labs, Stephen Batifol, Andreas Blattmann +18
We present evaluation results for FLUX.1 Kontext, a generative flow matching model that unifies image generation and editing. The model generates novel output views by incorporatin…
Oops, I Sampled it Again: Reinterpreting Confidence Intervals in Few-Shot Learning
Raphael Lafargue, Luke Smith, Franck Vermet +4
The predominant method for computing confidence intervals (CI) in few-shot learning (FSL) is based on sampling the tasks with replacement, i.e.\ allowing the same samples to appear…