SimonKohl/probabilistic_unet

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Language: Jupyter Notebook - Size: 21 MB - Last synced at: 4 days ago - Pushed at: over 2 years ago - Stars: 555 - Forks: 100

podgorskiy/GPND

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Language: Python - Size: 5.71 MB - Last synced at: 3 months ago - Pushed at: over 4 years ago - Stars: 129 - Forks: 31

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.

Language: Python - Size: 271 KB - Last synced at: 4 months ago - Pushed at: over 5 years ago - Stars: 114 - Forks: 41

XgDuan/WSDEC

Weakly Supervised Dense Event Captioning in Videos, i.e. generating multiple sentence descriptions for a video in a weakly-supervised manner.

Language: Python - Size: 482 KB - Last synced at: over 1 year ago - Pushed at: over 5 years ago - Stars: 103 - Forks: 26

woozzu/tagan

An official PyTorch implementation of the paper "Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language", NeurIPS 2018

Language: Python - Size: 3.5 MB - Last synced at: over 2 years ago - Pushed at: almost 6 years ago - Stars: 95 - Forks: 24

tlatkowski/inpainting-gmcnn-keras

Keras implementation of "Image Inpainting via Generative Multi-column Convolutional Neural Networks" paper published at NIPS 2018

Language: Python - Size: 7.59 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 94 - Forks: 39

wy1iu/MHE

Implementation for <Learning towards Minimum Hyperspherical Energy> in NIPS'18.

Language: Python - Size: 1.59 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 79 - Forks: 6

Ralmohsen/OSRAAE

Open-set Recognition with Adversarial Autoencoders

Language: Python - Size: 3.99 MB - Last synced at: 7 months ago - Pushed at: over 6 years ago - Stars: 37 - Forks: 12

shivamsaboo17/GLC

Gold Loss Correction for training neural networks with labels corrupted with severe noise

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RylanSchaeffer/HarvardAM207-prior-networks

Harvard Fall 2019 Applied Math 207 A Primer and Critique of Prior Networks

Language: Jupyter Notebook - Size: 53.2 MB - Last synced at: 6 days ago - Pushed at: over 5 years ago - Stars: 12 - Forks: 1

dist1ll/pomcpp

A re-implementation of the Pommerman environment in C++

Language: C++ - Size: 954 KB - Last synced at: 3 months ago - Pushed at: almost 4 years ago - Stars: 11 - Forks: 6

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"

Language: Python - Size: 91.5 MB - Last synced at: 1 day ago - Pushed at: over 6 years ago - Stars: 10 - Forks: 1

ermongroup/streamline-vi-csp

Language: C - Size: 2.32 MB - Last synced at: 3 months ago - Pushed at: over 6 years ago - Stars: 7 - Forks: 2

ethanhezhao/DirBN

The code for DirBN in NeurIPS 2018

Language: Matlab - Size: 49.1 MB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 7 - Forks: 4

jiahuei/report-nips-style

A LaTex template for reports, based on the elegant NIPS 2018 style.

Language: TeX - Size: 3.51 MB - Last synced at: over 2 years ago - Pushed at: over 5 years ago - Stars: 6 - Forks: 2

KMdsy/autowarp

Tensorflow implementation of paper ‘Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoder’ (NIPS18)

Language: Python - Size: 155 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 1

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

Our submission for the NeurIPs 2018: Adversarial Vision Challenge (Targeted Attack Track). Top-10 submission

Language: Python - Size: 358 MB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 2 - Forks: 0

BenjaminBush/skeletor

AI for Prosthetics NIPS 2018 Challenge. Repo created from helper: https://github.com/seungjaeryanlee/osim-rl-helper

Language: Jupyter Notebook - Size: 329 MB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 2 - Forks: 1

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.

Language: Jupyter Notebook - Size: 57.6 MB - Last synced at: about 1 month ago - Pushed at: about 5 years ago - Stars: 1 - Forks: 0

yashdusing/NIPS-2018-Challenge-Docker

The docker image of the NIPS 2018 challenge (no visualisations for now)

Language: Dockerfile - Size: 1000 Bytes - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0

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!

Language: Python - Size: 47.4 MB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0