Kahini Wadhawan (KahiniWadhawan)

KahiniWadhawan

User data from Github https://github.com/KahiniWadhawan

Company:IBM Research

Location:New York

GitHub:@KahiniWadhawan

Kahini Wadhawan's repositories

Big-Neuron

FAST processing of BIG data

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biomed_word_embeddings

Word embeddings for biomedical data

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biowordEmbeddings

Word Embeddings for Biomedical texts

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BlackBoxAuditing

Research code for auditing and exploring black box machine-learning models.

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controlled-text-generation

Reproducing Hu, et. al., ICML 2017's "Toward Controlled Generation of Text"

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CorefWiki

An application to detect Entity mentions in long texts such as Wikipedia and do computational analysis

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dcgan

Created for toolchain: https://console-regional.ng.bluemix.net/devops/toolchains/97f18842-5933-42e3-be13-fb8dd89e73b0

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DCGAN-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

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debiaswe

Remove problematic gender bias from word embeddings.

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demos

Demos and tutorials around Torch7.

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FireBal.github.io

kahini wadhawan blog

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MinasTirith

Quiz Bowl Kaggle competition "When to Buzz" code. Figure out the right answer to trivia questions! The goal of this project is to predict whether the answer to a trivia question is correct or not.

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MLProject_QB_Spring2015

Quiz Bowl- When They Buzz In-Class Kaggle project for Machine Learning course.

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Pubmed-Batch-Download

Batch download articles based on PMID (Pubmed ID)

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rl_tutorials

learning reinforcement learning from tutorials

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SeqGAN

Implementation of Sequence Generative Adversarial Nets with Policy Gradient

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text

Data loaders and abstractions for text and NLP

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torch-util

utility code for doing deep nlp in torch

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tutorials

A series of machine learning tutorials for Torch7

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VHRED-implementation-in-Tensorflow

A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues (VHRED) - Implementation in Tensorflow

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WGAN-tensorflow

a tensorflow implementation of WGAN

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word2vec

This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research.

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WordEmbeddings_BioNLP

Word Embeddings for Biomedical texts

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