koshinryuu's repositories

adversarial-multi-criteria-learning-for-CWS

The implementation of paper https://arxiv.org/abs/1704.07556, ACL 2017

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basilisk

BASILISK (Bootstrapping Approach to SemantIc Lexicon Induction using Semantic Knowledge)

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BREDS

Bootstrapping Relationship Extractors with Distributional Semantics

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chainer

A flexible framework of neural networks for deep learning

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end-to-end-negotiator

Deal or No Deal? End-to-End Learning for Negotiation Dialogues

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fairseq

Facebook AI Research Sequence-to-Sequence Toolkit

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fastText

Library for fast text representation and classification.

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generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

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iclr2016

Python code for training all models in the ICLR paper, "Towards Universal Paraphrastic Sentence Embeddings". These models achieve strong performance on semantic similarity tasks without any training or tuning on the training data for those tasks. They also can produce features that are at least as discriminative as skip-thought vectors for semantic similarity tasks at a minimum. Moreover, this code can achieve state-of-the-art results on entailment and sentiment tasks.

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InferSent

Sentence embeddings (InferSent) and training code for NLI.

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keras-gcn

Keras implementation of Graph Convolutional Networks

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nanoGPT

The simplest, fastest repository for training/finetuning medium-sized GPTs.

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neural-dep-srl

A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling

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pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

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pytorch-cn

Document for Pytorch project

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reinforcement-learning-an-introduction

Python code for Reinforcement Learning: An Introduction

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Seq2seq-Chatbot-for-Keras

This repository contains a new generative model of chatbot based on seq2seq modeling.

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Snowball

Snowball: Extracting Relations from Large Plain-Text Collections

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vecmap

A framework to learn bilingual word embedding mappings

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ViLT

Code for the ICML 2021 (long talk) paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

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