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Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…
ICLR 2021, Contrastive Learning with Hard Negative Samples
🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of feature importance for individual samples.
PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
A collection of implementations of adversarial domain adaptation algorithms
pytorch implementation of Domain-Adversarial Training of Neural Networks
A minimal pytorch package implementing a gradient reversal layer.
machine learning and deep learning tutorials, articles and other resources
Markdown export from Bear sqlite database
A Deep Learning Python Toolkit for Healthcare Applications.
A large-scale dataset of both raw MRI measurements and clinical MRI images.
Python wrapper module around kinit for simple Kerberos authentication.
Bash function to run tasks in parallel and display pretty output as they complete.
Dynamic evaluation for pytorch language models, now includes hyperparameter tuning
Random notes on papers, likely a short-term repo.
One-Shot Learning using Nearest-Neighbor Search (NNS) and Locality-Sensitive Hashing LSH
Official PyTorch implementation of Time-aware Large Kernel (TaLK) Convolutions (ICML 2020)
rectorch is a pytorch-based framework for state-of-the-art top-N recommendation
Simple ranking metrics for PyTorch on CPU or GPU
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch…
Fast Python Collaborative Filtering for Implicit Feedback Datasets
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.