Predict the effect of genetic mutations in cancer tumors and classify them based on text clinical literature.
-
Updated
Oct 7, 2020 - Jupyter Notebook
Predict the effect of genetic mutations in cancer tumors and classify them based on text clinical literature.
IPython Notebook showing pytorch implementation of Google DeepMind paper on Relation Network
Simple & Effective Dimensionality Reduction for Word Embeddings. Presented at NIPS 2017 LLLD & RepL4NLP 2019 Workshop.
analysis of configuration files in NIPS 2017 research repositories
Z-Forcing: Training Stochastic Recurrent Networks for Speech Modelling
Tensorflow Implementation of adversarial learning based adversarial example generator
An implementation of the "A simple neural network module for relational reasoning" paper in NIPS 2017
A collection of some nice papers/research articles.
Decathlon Multiple Visual Domains with Residual Adapters in Keras
NIPS 2017 Paper implementation challenge Learning Linear Dynamic Systems via Spectral Filtering
Chainer implementation of the paper "Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results" (https://arxiv.org/abs/1703.01780)
Selective Classification For Deep Neural Networks.
Fast-Slow Recurrent Neural Networks
Tensorflow Implementation of "Large-scale Optimal Transport and Mapping Estimation"(ICLR2018/NIPS 2017 OTML)
Reproduction code for WGAN-LP
Code for NIPS 2017 learning to run challenge
PyTorch re-implementation of parts of "Deep Sets" (NIPS 2017)
text convolution-deconvolution auto-encoder model in PyTorch
Add a description, image, and links to the nips-2017 topic page so that developers can more easily learn about it.
To associate your repository with the nips-2017 topic, visit your repo's landing page and select "manage topics."