Search Results for author:
Found 5 papers, 2 papers with code
From Charts to Atlas: Merging Latent Spaces into One
Models trained on semantically related datasets and tasks exhibit comparable inter-sample relations within their latent spaces.
From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication
It has been observed that representations learned by distinct neural networks conceal structural similarities when the models are trained under similar inductive biases.
LOB-Based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study
The recent advancements in Deep Learning (DL) research have notably influenced the finance sector.
Bootstrapping Parallel Anchors for Relative Representations
The use of relative representations for latent embeddings has shown potential in enabling latent space communication and zero-shot model stitching across a wide range of applications.
AI-based Data Preparation and Data Analytics in Healthcare: The Case of Diabetes
The Associazione Medici Diabetologi (AMD) collects and manages one of the largest worldwide-available collections of diabetic patient records, also known as the AMD database.
