XAI - An eXplainability toolbox for machine learning

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond

PyTorch implementation of Federated Learning algorithms FedSGD, FedAvg, FedAvgM, FedIR, FedVC, FedProx and standard SGD, applied to visual classification. Client distributions are synthesized with arbitrary non-identicalness and imbalance (Dirichlet priors). Client systems can be arbitrarily heterogeneous. Several mobile-friendly models are prov…

R wrapper for ENTSO-E Transparency Platform API — electricity prices, generation, load, cross-border flows

This repo contains implementation of advanced ML techniques. Includes model ensembles, cost-sensitive learning and dealing with class imbalance.

Estimation and correction of IQ imbalance in a QPSK modulation

Sampling-based methods for correcting for class imbalance in two-category classification problems

[AEPP 2022] Machine learning for food security: Principles for transparency and usability

REBAGG: REsampled BAGGing for Imbalanced Regression Tasks - LIDTA 2018

This project was made for classifying Covid and non-covid patients through cough sound. This is a non-invasive, inexpensive, and easy method so we can use that as the first filter

Loan Delinquency Prediction from Analytics Vidya

Predict employee turnover with sci-kit learn in python

In class Kaggle competition on predicting bankruptcy of a firm

This work focuses on the development of machine learning models, in particular neural networks and SVM, where they can detect toxicity in comments. The topics we will be dealing with: a) Cost-sensitive learning, b) Class imbalance

Nordic power trading tools (SE3/SE4): imbalance heatmaps, DA↔imbalance, spread monitor, battery-lite sim.

Predicting categories of scientific papers with advanced machine learning techniques involving class imbalance in multi-label data and explainable machine learning.

Coursework for the class IT3030 - Deep learning, taken during Spring 2022

MSc Artificial Intelligence Thesis at the UvA in collaboration with the City of Amsterdam. The project concerns the improvement of semantic segmentation quality of underrepresented objects in imbalanced urban point clouds.

polymarket order book imbalance bot, Node/TypeScript trading bot for Polymarket’s CLOB. Subscribes to the market WebSocket, measures bid vs ask liquidity in a band around the mid, enters on strong imbalance (e.g. thin ask), exits when the book normalizes or on take-profit. Dry-run by default; wallet optional for live FAK orders.