16 skills found
pcko1 / Deep Drug CoderA tensorflow.keras generative neural network for de novo drug design, first-authored in Nature Machine Intelligence while working at AstraZeneca.
ndrplz / Dilation TensorflowA native Tensorflow implementation of semantic segmentation according to Multi-Scale Context Aggregation by Dilated Convolutions (2016). Optionally uses the pretrained weights by the authors.
MKLab-ITI / Ndvr DmlAuthors official Tensorflow implementation of the "Near-Duplicate Video Retrieval with Deep Metric Learning" [ICCVW 2017]
WindQAQ / Listen Attend And SpellTensorflow implementation of "Listen, Attend and Spell" authored by William Chan. This project utilizes input pipeline and estimator API of Tensorflow, which makes the training and evaluation truly end-to-end.
zacheberhart / Maximum Mean Discrepancy Variational AutoencoderA PyTorch implementation of the MMD-VAE, an Information-Maximizing Variational Autoencoder (InfoVAE) based off of the TensorFlow implementation published by the author of the original InfoVAE paper.
mever-team / AusilAuthors official Tensorflow implementation of the "Audio-based Near-Duplicate Video Retrieval with Audio Similarity Learning" [ICPR 2020]
pouyaardehkhani / ActTensorActTensor: Activation Functions for TensorFlow. https://pypi.org/project/ActTensor-tf/ Authors: Pouya Ardehkhani, Pegah Ardehkhani
Ritik2703 / Coursera Natural Language Processing Specialization By Deeplearning.AI#Assignment Answers #About this Specialization: Natural Language Processing (NLP) uses algorithms to understand and manipulate human language. This technology is one of the most broadly applied areas of machine learning. As AI continues to expand, so will the demand for professionals skilled at building models that analyze speech and language, uncover contextual patterns, and produce insights from text and audio. By the end of this Specialization, you will be ready to design NLP applications that perform question-answering and sentiment analysis, create tools to translate languages and summarize text, and even build chatbots. These and other NLP applications are going to be at the forefront of the coming transformation to an AI-powered future. This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper.
msraig / InexactSAAuthors' TensorFlow implementation for PG2018 paper "Single Image Surface Appearance Modeling with Self-augmented CNNs and Inexact Supervision"
fish233yeah / PINNs Implemented By PytorchAfter reading the paper Physics-informed neural networks(https://www.sciencedirect.com/science/article/pii/S0021999118307125), I tried to fit heat equation and wave equation with pytorch (while the author used the tensorflow), and certainly these code can be used to fit other equations
armando-fandango / Mastering TensorFlowAuthor's copy of the Mastering TensorFlow Book's Repo
ralphcajipe / Machine Learning With PythonThese Colab notebooks are fundamental concepts and methods in Machine Learning & Artificial Intelligence using Google's TensorFlow 2.0 library. Authored by Tim Ruscica at freeCodeCamp.org for Machine Learning with Python course.
Quantum-Software-Development / .github🇶 Quantum 4 All - Research and Exploration in the Field of Quantum Computing
yourgone / Graph Deep LearningImplementations of various graph node embeddings and benchmark graph neural network models using TensorFlow. This repository is based on a Kaggle notebook (originally authored by abhilash1910) showcasing how to apply GNNs/node embeddings on NLP tasks.
Anton-Ding / Partical InteractionInteractive gesture-driven particle visualization built with Three.js, TensorFlow.js, and MediaPipe. Non-commercial use only; commercial licensing requires author permission.
malakalmarshad / TOSAThis repository contains the source code related to our paper "Transformer-based Deep Learning Approach for Obstructive Sleep Apnea Detection Using Single-lead ECG", authored by Malak Abdullah Almarshad, Saad Al-Ahmadi, Md Saiful Islam, Adel Soudani, Ahmed S BaHammam. The code is designed to run on TensorFlow 2.10, exploiting GPUs.
