Bernhard Kratzwald

qa-annotation. PyTorch implementation of the EMNLP 2020 paper Learning a Cost-Effective Annotation Policy for Question Answering

django-video. A simple Video Streaming application for Django.

maskrcnn-benchmark. Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

FastMaskRCNN. Mask RCNN in TensorFlow

py-faster-rcnn. Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version

transferlearning. Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

PaDiM-Anomaly-Detection-Localization-master. This is an unofficial implementation of the paper “PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization”.

intkb. This is the Python implementation of the COLING 2020 paper "IntKB: A Verifiable Interactive Framework for Knowledge Base Completion"

CascadeLSTM. A tree-structured neural classifier for detecting misinformation cascades

ml-fairness-gym. Python

Group-Meeting-Reading. https://sunlab-osu.github.io/Group-Meeting-Reading/

gpt-2-simple. Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts

PathNet. PathNet model for Multi-hop Reading Comprehension (https://arxiv.org/pdf/1811.01127.pdf)

DecompRC. An original implementation of ACL 2019, "Multi-hop Reading Comprehension through Question Decomposition and Rescoring"

MLSS2019_notes.

autograd. Efficiently computes derivatives of NumPy code.

lectures. repository with the lectures for MLSS Skoltech

MultiQA. Python

tutorials. repository with the tutorials for MLSS Skoltech

MUPPET. Code for the paper "multi-hop paragraph retrieval for open-domain question answering"

MeQSum. Dataset for medical question summarization introduced in the ACL 2019 paper "On the Summarization of Consumer Health Questions" (A. Ben Abacha & D. Demner-Fushman)

emr. Code for Episodic Memory Reader (EMR) https://arxiv.org/abs/1903.06164

caffeR. R

LSTM_imdb. Python

ParagraphRanker. EMNLP'2018: Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answering

MarketBasket. Personalized Purchase Prediction of Market Baskets with Wasserstein-Based Sequence Matching

improved-video-gan. GitHub repository for "Improving Video Generation for Multi-functional Applications"

mord. Ordinal regression algorithms

gamelab_spring2016.

dataset-factoid-curated. A curated question answering research dataset of factoid questions

lucene4ir. Lucene for Information Retrieval

DynSLAM. Master's Thesis on Simultaneous Localization and Mapping in dynamic environments. Separately reconstructs both the static environment and the dynamic objects from it, such as cars.

FinancialDeepLearning. Decision support from financial disclosures with deep neural networks and transfer learning

bi-att-flow. Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.

BEGAN-tensorflow. python3 / Implementation of Google Brain's BEGAN in Tensorflow

BEGAN-tensorflow. Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"

WassersteinGAN. Python

videogan. Generating Videos with Scene Dynamics. NIPS 2016.

visualqa. Visual Question Answering project for ETHZ's 2016/17 Deep Learning class.

twitter-sentiment-analysis. Twitter Sentiment Analysis with Deep Convolutional Neural Networks and LSTMs in TensorFlow.

scikit-learn-contrib. scikit-learn compatible projects

eth-nlp-project. An Improvement of SMAPH-S for Entity Linking of Web Queries

numpy. The fundamental package for scientific computing with Python.

notebooks. jupyter notebooks on machine learning, computational intelligence and statistics..

cil-exercises. ETH Zurich, Computational Intelligence Lab exercises

scikit-learn. scikit-learn: machine learning in Python