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Image Colorization with Generative Adversarial Networks
Over the last decade, the process of automatic image colorization has been of significant interest for several application areas including restoration of aged or degraded images.
Learning and Evaluating Contextual Embedding of Source Code
We fine-tune CuBERT on our benchmark tasks, and compare the resulting models to different variants of Word2Vec token embeddings, BiLSTM and Transformer models, as well as published state-of-the-art models, showing that CuBERT outperforms them all, even with shorter training, and with fewer labeled examples.
Dlib-ml: A Machine Learning Toolkit
There are many excellent toolkits which provide support for developing machine learning software in Python, R, Matlab, and similar environments.
Ranked #3 on
Face Verification
on Labeled Faces in the Wild
(using extra training data)
Layered TPOT: Speeding up Tree-based Pipeline Optimization
With the demand for machine learning increasing, so does the demand for tools which make it easier to use.
SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
SciPy is an open source scientific computing library for the Python programming language.
Mathematical Software Data Structures and Algorithms Software Engineering Computational Physics
Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System
Taskflow introduces an expressive task graph programming model to assist developers in the implementation of parallel and heterogeneous decomposition strategies on a heterogeneous computing platform.
SQLFlow: A Bridge between SQL and Machine Learning
Previous database systems extended their SQL dialect to support ML.
Solving Mixed Integer Programs Using Neural Networks
Our approach constructs two corresponding neural network-based components, Neural Diving and Neural Branching, to use in a base MIP solver such as SCIP.
mlpack 3: a fast, flexible machine learning library
In the past several years, the field of machine learning has seen an explosion of interest and excitement, with hundreds or thousands of algorithms developed for different tasks every year.
Towards Automatic Learning of Heuristics for Mechanical Transformations of Procedural Code
Program transformation systems require the definition of efficient transformation strategies to tackle the combinatorial problem that emerges due to the large set of transformations applicable at each step of the process.
