Exploring possible solutions for NIPS2018 challenge. This repo is for convenience of exchanging test result / code, it's updated lazily on demand!

Code, documents, and deployment configuration files, related to our participation in the 2018 NIPS Adversarial Vision Challenge "Robust Model Track"

The code for DirBN in NeurIPS 2018

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

Open-set Recognition with Adversarial Autoencoders

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

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

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

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

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.

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

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

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

Using LDA, we analyze a large collection of NIPS research papers from the past 3 decades, o discover the latest trends in machine learning.

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

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

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

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

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