AmeniTrabelsi

deep_intent

Modeling pedestrian and vehicular movement to determine stochastic response to anomalies

DeepBind-with-PyTorch

PyTorch implementation of a DeepBind model

DeepBind_with_Tensorflow

Implementation of Deepbind using TensorFlow

Image_Annotation_Based_on_Partially_Labeled_Data

Algorithm for annotating new-to-the-system image regions based on images from Corel Dataset

KEGRU_with_Pytorch

MILIS

Multiple Instance Learning with Instance Selection

Molecule-Specific-Normalization

Normalization algorithm for proteomics and metabolomics data

RNA

create rna db

TensorFlow-Tutorials

Simple Examples with TensorFlow from scratch

deepRAM

End-to-end deep learning toolkit for predicting protein binding sites and motifs.

AmeniTrabelsi/DeepBind_with_Tensorflow

Implementation of Deepbind using TensorFlow

AmeniTrabelsi/Molecule-Specific-Normalization

Normalization algorithm for proteomics and metabolomics data

AmeniTrabelsi/Image_Annotation_Based_on_Partially_Labeled_Data

Algorithm for annotating new-to-the-system image regions based on images from Corel Dataset

AmeniTrabelsi/MILIS

Multiple Instance Learning with Instance Selection

AmeniTrabelsi/RNA

create rna db

AmeniTrabelsi/deep_intent

Modeling pedestrian and vehicular movement to determine stochastic response to anomalies

AmeniTrabelsi/DeepBind-with-PyTorch

PyTorch implementation of a DeepBind model

AmeniTrabelsi/KEGRU_with_Pytorch

AmeniTrabelsi/TensorFlow-Tutorials

Simple Examples with TensorFlow from scratch

AmeniTrabelsi/iDeep

iDeep: integrated prediction of RNA-protein binding sites using deep learning

AmeniTrabelsi/Master-Thesis

AmeniTrabelsi/pipeline

PipelineAI: Real-Time Enterprise AI Platform