nips-2018

There are 4 repositories under nips-2018 topic.

SimonKohl / probabilistic_unet
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
u-net variational-inference semantic-segmentation generative-models variational-autoencoders neurips neurips-2018 nips nips-2018
Language:Jupyter Notebook 562
podgorskiy / GPND
Generative Probabilistic Novelty Detection with Adversarial Autoencoders
deep-learning deep-neural-networks deep-novelty-detection novelty-detection anomaly-detection adversarial-learning autoencoder pytorch generative-adversarial-network gan adversarial-autoencoders probability aae novelty-detector mnist pdf machine-learning nips-2018
Language:Python 131
flytxtds / AutoGBT
AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-drift. AutoGBT was developed by a joint team ('autodidact.ai') from Flytxt, Indian Institute of Technology Delhi and CSIR-CEERI as a part of NIPS 2018 AutoML for Lifelong Machine Learning Challenge.
automl concept-drift nips-2018 lifelong-ml hyperopt
Language:Python 114
XgDuan / WSDEC
Weakly Supervised Dense Event Captioning in Videos, i.e. generating multiple sentence descriptions for a video in a weakly-supervised manner.
videocaptioning weakly-supervised-learning nips-2018
Language:Python 104
woozzu / tagan
An official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018
gan gans generative-adversarial-network manipulate-images natural-language nips-2018 neurips-2018 text-to-image
Language:Python 95
tlatkowski / inpainting-gmcnn-keras
Keras implementation of "Image Inpainting via Generative Multi-column Convolutional Neural Networks" paper published at NIPS 2018
inpainting keras deep-learning nips-2018 gan generative-adversarial-network convolutional-neural-networks tensorflow computer-vision cnn python3 wasserstein-gan wgan-gp image-inpainting deep-neural-networks improved-wgan improved-wasserstein neurips-2018 places365 nvidia
Language:Python 94
wy1iu / MHE
Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.
mhe nips-2018 minimum-hyperspherical-energy sphereface sphereface-plus thomson-regularization
Language:Python 80
Ralmohsen / OSRAAE
Open-set Recognition with Adversarial Autoencoders
deep-learning deep-neural-networks deep-novelty-detection novelty-detection anomaly-detection adversarial-learning autoencoder pytorch generative-adversarial-network gan adversarial-autoencoders probability aae novelty-detector mnist machine-learning nips-2018 wiml
Language:Python 39
shivamsaboo17 / GLC
Gold Loss Correction for training neural networks with labels corrupted with severe noise
pytorch deep-learning classification noisy-labels nips-2018
Language:Jupyter Notebook 13
RylanSchaeffer / HarvardAM207-prior-networks
Harvard Fall 2019 Applied Math 207 A Primer and Critique of Prior Networks
neurips-2018 nips-2018 nips prior-networks bayesian-neural-networks
Language:Jupyter Notebook 12
dist1ll / pomcpp
A re-implementation of the Pommerman environment in C++
reinforcement-learning nips-2018
Language:C++ 11
Simsso / NIPS-2018-Adversarial-Vision-Challenge
Code, documents, and deployment configuration files, related to our participation in the 2018 NIPS Adversarial Vision Challenge "Robust Model Track"
nips-2018 adversarial-attacks classifier robustness tensorflow
Language:Python 10
jiahuei / report-nips-style
A LaTex template for reports, based on the elegant NIPS 2018 style.
latex latex-template latex-style arxiv paper research-paper preprints sty nips-2018 nips nips-style nips-styling
Language:TeX 9
ermongroup / streamline-vi-csp
variational-inference constraint-satisfaction-problem satisfiability belief-propagation sat-solver nips-2018
Language:C 7
ethanhezhao / DirBN
The code for DirBN in NeurIPS 2018
topic-modeling machine-learning bayesian-statistics nips-2018 bayesian-nonparametrics
Language:MATLAB 7
KMdsy / autowarp
Tensorflow implementation of paper ‘Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoder’ (NIPS18)
time-series nips-2018 similarity-metric deep-learning
Language:Python 4
BenjaminBush / skeletor
AI for Prosthetics NIPS 2018 Challenge. Repo created from helper: https://github.com/seungjaeryanlee/osim-rl-helper
deep-reinforcement-learning nips-2018 dqn a3c ddpg ppo
Language:Jupyter Notebook 2
IsCoelacanth / NeurIPS-2018-Adversarial-Vision-Challenge-Targeted-Attack
Our submission for the NeurIPs 2018: Adversarial Vision Challenge (Targeted Attack Track). Top-10 submission
adversarial-attacks tensorflow nips-2018
Language:Python 2
pranavtumkur / Analyzing-the-Hottest-Topics-in-ML-using-LDA
Using LDA, we analyze a large collection of NIPS research papers from the past 3 decades, o discover the latest trends in machine learning.
lda latent-dirichlet-allocation machine-learning nips-2018 ml
Language:Jupyter Notebook 1
smdsbz / NIPS2018-test-solution
Exploring possible solutions for NIPS2018 challenge. This repo is for convenience of exchanging test result / code, it's updated lazily on demand!
nips-2018 deep-reinforcement-learning machine-learning titan-v
Language:Python
yashdusing / NIPS-2018-Challenge-Docker
The docker image of the NIPS 2018 challenge (no visualisations for now)
docker-image nips-2018
Language:Dockerfile

nips-2018

SimonKohl / probabilistic_unet

podgorskiy / GPND

flytxtds / AutoGBT

XgDuan / WSDEC

woozzu / tagan

tlatkowski / inpainting-gmcnn-keras

wy1iu / MHE

Ralmohsen / OSRAAE

shivamsaboo17 / GLC

RylanSchaeffer / HarvardAM207-prior-networks

dist1ll / pomcpp

Simsso / NIPS-2018-Adversarial-Vision-Challenge

jiahuei / report-nips-style

ermongroup / streamline-vi-csp

ethanhezhao / DirBN

KMdsy / autowarp

BenjaminBush / skeletor

IsCoelacanth / NeurIPS-2018-Adversarial-Vision-Challenge-Targeted-Attack

pranavtumkur / Analyzing-the-Hottest-Topics-in-ML-using-LDA

smdsbz / NIPS2018-test-solution

yashdusing / NIPS-2018-Challenge-Docker