Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
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Updated
Jul 10, 2018 - Python
Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
📈 SiRE (Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data), accepted by CIKM'2022 🗽
Runner-up team (2nd place) in AI4VN2022: Air Quality Forcasting Challenge
Implementation of the Smith-Wilson yield curve fitting algorithm in Python for interpolations and extrapolations of zero-coupon bond rates
Popular way to model the yield curve called Nelson-Siegel-Svannson algorithm.
Deep 3D Semantic Scene Extrapolation
Implementation of the Smith & Wilson algorithm for interpolation and/or extrapolation of missing interest rates in Python.
Obstruction-Aware Signal-Loss-Tolerant Indoor Positioning (OASLTIP) Using Bluetooth Low Energy
[ICML23] Extrapolated Random Tree for Regression
A toolkit for the study of periodicity (especially periodic extrapolation) in neural networks
Python library for radar Bandwidth Extrapolation (BWE)
Predict IPL scores of teams based on past performance
Simple bisection method that finds the optimal parameter α for the Smith & Wilson algorithm.
Modeling defocus blur with linearity constraints in the latent space
Algoritmo popolare per adattare una curva dei rendimenti a dati osservati.
Applied Mathematics(Numerical Methods or Numerical Analysis) TW324.
Extrapolated Tree
Extrapolation of COVID19 Infections
An unofficial refactor of the code used by the ICML 2020 paper "Continuously Indexed Domain Adaptation"
predict the IPL score of the team based on the past performance.
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