1 code implementation • 29 Nov 2021 • Oskar Triebe, Hansika Hewamalage, Polina Pilyugina, Nikolay Laptev, Christoph Bergmeir, Ram Rajagopal
NeuralProphet is a hybrid forecasting framework based on PyTorch and trained with standard deep learning methods, making it easy for developers to extend the framework.
no code implementations • 25 Jun 2020 • Paulo Tanaka, Sameet Sapra, Nikolay Laptev
Content based data classification is an open challenge.
2 code implementations • 27 Nov 2019 • Oskar Triebe, Nikolay Laptev, Ram Rajagopal
In this paper we present a new framework for time-series modeling that combines the best of traditional statistical models and neural networks.
6 code implementations • 6 Sep 2017 • Lingxue Zhu, Nikolay Laptev
Reliable uncertainty estimation for time series prediction is critical in many fields, including physics, biology, and manufacturing.
Ranked #1 on Time Series Forecasting on Hurricane
no code implementations • 16 May 2017 • Jeya Balaji Balasubramanian, Akshay Soni, Yashar Mehdad, Nikolay Laptev
The content ranking problem in a social news website, is typically a function that maximizes a scalar metric of interest like dwell-time.
no code implementations • 24 Feb 2017 • Swayambhoo Jain, Akshay Soni, Nikolay Laptev, Yashar Mehdad
For many internet businesses, presenting a given list of items in an order that maximizes a certain metric of interest (e. g., click-through-rate, average engagement time etc.)