valeman's Projects
Repository of the ICML 2020 paper "Set Functions for Time Series"
Scalable Time Series Data Analytics
The Shogun Machine Learning Toolbox (Source Code)
sidetable builds simple but useful summary tables of your data
A simplistic linear and multiprocessed approach to sentiment analysis using Gzip Normalized Compression Distances with k nearest neighbors
📈 SiRE (Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series Data), accepted by CIKM'2022 🗽
SKAB - Skoltech Anomaly Benchmark. Time-series data for evaluating Anomaly Detection algorithms.
Time series forecasting with scikit-learn models
The dataset consists of 10015 dermatoscopic images which can serve as a training set for academic machine learning purposes. The objective to build deep learning model to classify given query image into one of the 7 different classes of skin cancer.
A centralized repository to report scikit-learn model performance across a variety of parameter settings and data sets.
A unified framework for tabular probabilistic regression and probability distributions in python
A scikit-learn compatible Python toolbox for learning with time series data
sktime companion package for deep learning based on TensorFlow
sktime - python toolbox for time series: pipelines and transformers
skbase - a workbench for creating scikit-learn like parametric objects and libraries
It'll detect your anomalies! Part of the Kale stack.
Conformal Prediction with Localized De-correlation
Sequential Model-based Algorithm Configuration
Statistical Machine Intelligence & Learning Engine
Code for Master's dissertation: Solar Radiation Forecasting with Deep Learning and Conformal Prediction
Core data gathering, validation, processing, and reporting package for the Solar Forecast Arbiter
Returns latest research results by crawling arxiv papers and summarizing abstracts. Helps you stay afloat with so many new papers everyday.
Code for SpaceTime 🌌⏱️. Proposed in Effectively Modeling Time Series with Simple Discrete State Spaces, ICLR 2023.
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."