2 citations · 4 across the 12 of their papers we have counts for
13 papers
Early Risk Stratification of Dosing Errors in Clinical Trials Using Machine Learning
Félicien Hêche, Sohrab Ferdowsi, Anthony Yazdani +2
Objective: The objective of this study is to develop a machine learning (ML)-based framework for early risk stratification of clinical trials (CTs) according to their likelihood of…
Classification of hierarchical text using geometric deep learning: the case of clinical trials corpus
Sohrab Ferdowsi, Nikolay Borissov, Julien Knafou +2
We consider the hierarchical representation of documents as graphs and use geometric deep learning to classify them into different categories. While graph neural networks can effic…
Privacy-Preserving Near Neighbor Search via Sparse Coding with Ambiguation
Behrooz Razeghi, Sohrab Ferdowsi, Dimche Kostadinov +2
In this paper, we propose a framework for privacy-preserving approximate near neighbor search via stochastic sparsifying encoding. The core of the framework relies on sparse coding…
Privacy-Preserving Image Sharing via Sparsifying Layers on Convolutional Groups
Sohrab Ferdowsi, Behrooz Razeghi, Taras Holotyak +2
We propose a practical framework to address the problem of privacy-aware image sharing in large-scale setups. We argue that, while compactness is always desired at scale, this need…
-VAE: Autoregressive parametrization of the VAE encoder
Sohrab Ferdowsi, Maurits Diephuis, Shideh Rezaeifar +1
We make a minimal, but very effective alteration to the VAE model. This is about a drop-in replacement for the (sample-dependent) approximate posterior to change it from the standa…
Learning to compress and search visual data in large-scale systems
Sohrab Ferdowsi
The problem of high-dimensional and large-scale representation of visual data is addressed from an unsupervised learning perspective. The emphasis is put on discrete representation…