Neural question generation using transformers
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Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
- seq2seq
- tensorflow
- tensorflow-tutorials
- python
"Neural Turing Machine" in Tensorflow
- tensorflow
- neural-turing-machines
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano
A knowledge graph and a set of tools for drug repurposing
- drug-repurposing
- knowledge-graph
- graph-neural-networks
- knowledge-graph-embeddings
food image to recipe with deep convolutional neural networks.
- convolutional-neural-networks
- keras
- chef
- deep-learning
Solve captcha without manually labeling a training set
- keras
- gan
- neural-network
- generative-adversarial-network
This repository contains notebooks that show the usage of TensorFlow Lite for quantizing deep neural networks.
- tensorflow-2
- tensorflow-lite
- on-device-ml
- model-quantization
Optimising chemical reactions using machine learning
- chemistry
- machine-learning
- optimization
- bayesian-optimization
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
- probabilistic-programming
- neural-network
- tensorflow
- keras-tensorflow
Deep learning model for single-cell inference of multi-omic profiles from a single input modality.
- single-cell
- scrna-seq
- scatac-seq
- deep-neural-networks
Deciphering cell-cell communication from spatially resolved transcriptomic data at single-cell resolution with subgraph-based attentional graph neural network
Implementation of "Adversarial Frontier Stitching for Remote Neural Network Watermarking" in TensorFlow.
- tensorflow
- tensorflow2
- watermarking
- neural-network
Attempt at reproducing a SGNN's projection layer, but with word n-grams instead of skip-grams. Paper and more: http://aclweb.org/anthology/D18-1105
Interpretable drug response prediction with graph neural networks over drugs, cell lines, and genes.