TensorFlow is a powerful open-source software library for dataflow programming across a range of tasks. Below is a curated list of research papers related to TensorFlow. For more in-depth understanding, check out our TensorFlow Papers.
Deep Learning for Time Series Classification: A Review
This paper provides a comprehensive review of deep learning approaches for time series classification.TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems
This paper introduces TensorFlow and its architecture, which enables large-scale machine learning on a variety of distributed systems.Recurrent Neural Networks for Language Modeling
This paper discusses the use of recurrent neural networks for language modeling, a fundamental task in natural language processing.Generative Adversarial Nets
This paper introduces Generative Adversarial Networks (GANs), a framework for training generative models capable of producing high-quality samples.TensorFlow for Image Recognition
This paper demonstrates how TensorFlow can be used for image recognition tasks, including convolutional neural networks.
Read more about TensorFlow research.
Key Papers
Deep Learning with TensorFlow
A practical guide to deep learning using TensorFlow.TensorFlow Papers
A collection of TensorFlow-related research papers.