Flow-based generative models are a family of exact log-likelihood models withtractable sampling and latent-variable inference, hence conceptually attractive formodeling complex distributions. However, flow-based models are limited by den-sity estimation performance issues as compared to state-of-the-art autoregressivemodels. Autoregressive models, which also belong to the family of likelihood-based methods, however suffer from limited parallelizability. In this paper, weproposeDynamic Linear Flow (DLF), a new family of invertible transformationswith partially autoregressive structure. Our method benefits from the efficientcomputation of flow-based methods and high density estimation performance ofautoregressive methods. We demonstrate that the proposed DLF yields state-of-the-art performance on ImageNet 32×32 and 64×64 out of all flow-based methods,and is competitive with the best autoregressive model. Additionally, our modelconverges 10 times faster than Glow (Kingma and Dhariwal, 2018). The code isavailable athttps://github.com/naturomics/DLF

Do not miss out on this unique opportunity to get insights from Tarry Singh, leader in AI training and technology. Tarry will share with you his insight and methods for transforming midsize as well as large companies into functioning AI companies in the Europe. Now we are bringing our expertise to Japan! Together with our Country Director we will expand our services in the Japan that will provide enterprise advisory as well as unique AI trainings pertaining to Big Data, Machine Learning and Deep Learning.

Do not miss out on this unique opportunity to get insights from Tarry Singh, leader in AI training and technology. Tarry will share with you his insight and methods for transforming midsize as well as large companies into functioning AI companies in the Europe. Now we are bringing our expertise to The Netherlands! We at deepkapha.ai are delighted to announce our AI training partnership with Startel.  Our CEO Tarry Singh and Startel CEO Marco Wagenveld have combined forces to provide unique AI trainings pertaining to Big Data, Machine Learning and Deep Learning.

deepkapha.ai delivered a 2-day hands-on technical workshop on Deep Learning to some bright minds in Finland. These were from various industry and government areas such as manufacturing, telecom, defense, healthcare and more.

In this lecture we discussed the newly released capsule network by Geoffrey Hinton and his co-authors. Capsule networks is the new and shiny neural network architecture that is challenging CNN, currently the king of the hill in computer vision.

deepkapha.ai was proud to have been both program committee member and presenter at SEC4COG workshop of our breakthrough neuroscience research paper during the 40th International Conference on Software Engineering, May 27 – 3 June 2018, Gothenburg, Sweden.

deepkapha.ai was invited to deliver a talk at meetupai.com, a community driven AI Conference setup by Rico Meihl and his associates.

deepkapha.ai participated with several other prominent researchers from Germany, Italy to give a dedicated deep learning bioinformatics workshop.

This was a great event organised by a few prominent universities in Berlin, Germany (Humboldt University, Charite, FreiUniversitait)