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nikolausn's Projects

aat icon aat

Code for paper "Adaptively Aligned Image Captioning via Adaptive Attention Time". NeurIPS 2019

academic-portfolio icon academic-portfolio

A one-stop, clean and minimal mobile-friendly Jekyll theme for your academic homepage

aix360 icon aix360

Interpretability and explainability of data and machine learning models

albert icon albert

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

all-about-xai icon all-about-xai

This repository is all about papers and tools of Explainable AI

amr-gs icon amr-gs

AMR Parsing via Graph-Sequence Iterative Inference

amr-parser icon amr-parser

AMR-parser. Code for EMNLP2019 paper "Core Semantic First: A Top-down Approach for AMR Parsing."

attend2u icon attend2u

🖼️ Attend to You: Personalized Image Captioning with Context Sequence Memory Networks. In CVPR, 2017. Expanded : Towards Personalized Image Captioning via Multimodal Memory Networks. In IEEE TPAMI, 2018.

attentionwalk icon attentionwalk

A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).

awesome-pytorch-list icon awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

bert-as-service icon bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

bertsearch icon bertsearch

Elasticsearch with BERT for advanced document search.

biobert icon biobert

BioBERT: a pre-trained biomedical language representation model

bionev icon bionev

Graph Embedding Evaluation / Code and Datasets for "Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations"

cnn-dailymail icon cnn-dailymail

Code to obtain the CNN / Daily Mail dataset (non-anonymized) for summarization

cnn-exposed icon cnn-exposed

🕵️‍♂️ Interpreting Convolutional Neural Network (CNN) Results.

coclean icon coclean

CoClean: Collaborative Data Cleaning

codet5 icon codet5

Home of CodeT5: Open Code LLMs for Code Understanding and Generation

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