Pinned Repositories
cclust_package
clean-code-ml
:bathtub: Clean Code concepts adapted for machine learning and data science
DETM
ETM
Topic Modeling in Embedding Spaces
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.
multisense-prob-fasttext
ACL 2018 paper: Probabilistic FastText for Multi-Sense Word Embeddings (Athiwaratkun et al., 2018)
P-SIF
Source code for P-SIF Document Embedding (AAAI 2020)
SIF
sentence embedding by Smooth Inverse Frequency weighting scheme
word2gm
Word to Gaussian Mixture Model
mchaduteau's Repositories
mchaduteau/cclust_package
mchaduteau/clean-code-ml
:bathtub: Clean Code concepts adapted for machine learning and data science
mchaduteau/DETM
mchaduteau/ETM
Topic Modeling in Embedding Spaces
mchaduteau/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.
mchaduteau/multisense-prob-fasttext
ACL 2018 paper: Probabilistic FastText for Multi-Sense Word Embeddings (Athiwaratkun et al., 2018)
mchaduteau/P-SIF
Source code for P-SIF Document Embedding (AAAI 2020)
mchaduteau/SIF
sentence embedding by Smooth Inverse Frequency weighting scheme
mchaduteau/word2gm
Word to Gaussian Mixture Model