In this paper, we present Theano1, a framework in the Python programming language for defining, optimizing and evaluating expressions involving high-level operations on ten-sors. Theano offers most of NumPy’s functionality, but adds automatic symbolic differen-tiation, GPU support, and faster expression evaluation. Theano is a general mathematical tool, but it was developed with the goal of facilitating research in deep learning. The Deep Learning Tutorials2 introduce recent advances in deep learning, and showcase how Theano makes such algorithms compact, elegant, and fast
2019 IEEE. Artificial intelligence based on deep learning has gained popularity in a broad range of ...
We present a library that provides optimized implementations for deep learning primitives. Deep lear...
Abstract Graphics processing units (GPUs) have tremendous computing power, but are hard to program. ...
Abstract—Theano is a compiler for mathematical expressions in Python that combines the convenience o...
Abstract Theano is a linear algebra compiler that optimizes a user's symbolically-specified mat...
Deep learning techniques have proven to be very successful when dealing with highly-complex problems...
We present a new tool for training neural network language models (NNLMs), scoring sentences, and ge...
This book explains the essential learning algorithms used for deep and shallow architectures. Packed...
Theano is a linear algebra compiler that optimizes a user’s symbolically-specified mathematical comp...
GPU technologies are the paradigm shift in modern computing. This book will take you through archite...
International audienceGeometric methods rely on tensors that can be encoded using a symbolic formula...
This tutorial will introduce the latest deep learning software packages and explain how to get start...
There are many successful applications to take advantages of massive parallelization on GPU for deep...
In this paper, we present PARTIME, a software library written in Python and based on PyTorch, design...
Abstract. One of the major research trends currently is the evolution of heterogeneous parallel comp...
2019 IEEE. Artificial intelligence based on deep learning has gained popularity in a broad range of ...
We present a library that provides optimized implementations for deep learning primitives. Deep lear...
Abstract Graphics processing units (GPUs) have tremendous computing power, but are hard to program. ...
Abstract—Theano is a compiler for mathematical expressions in Python that combines the convenience o...
Abstract Theano is a linear algebra compiler that optimizes a user's symbolically-specified mat...
Deep learning techniques have proven to be very successful when dealing with highly-complex problems...
We present a new tool for training neural network language models (NNLMs), scoring sentences, and ge...
This book explains the essential learning algorithms used for deep and shallow architectures. Packed...
Theano is a linear algebra compiler that optimizes a user’s symbolically-specified mathematical comp...
GPU technologies are the paradigm shift in modern computing. This book will take you through archite...
International audienceGeometric methods rely on tensors that can be encoded using a symbolic formula...
This tutorial will introduce the latest deep learning software packages and explain how to get start...
There are many successful applications to take advantages of massive parallelization on GPU for deep...
In this paper, we present PARTIME, a software library written in Python and based on PyTorch, design...
Abstract. One of the major research trends currently is the evolution of heterogeneous parallel comp...
2019 IEEE. Artificial intelligence based on deep learning has gained popularity in a broad range of ...
We present a library that provides optimized implementations for deep learning primitives. Deep lear...
Abstract Graphics processing units (GPUs) have tremendous computing power, but are hard to program. ...