The Sensor Fault Detection system is designed to monitor sensors and detect any faults. It uses advanced algorithms to ensure the accuracy and reliability of sensor data.

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation

Unsupervised Anomaly Detection System for Univariate Time Series

[CVPR 2024 Oral - Best paper award candidate] Official repository of "PaSCo: Urban 3D Panoptic Scene Completion with Uncertainty Awareness"

CAVAanalytics is a comprehensive framework for climate data analysis, offering streamlined access to data, advanced processing and visualization capabilities. It is designed to support a wide range of climate research and user needs

This model utilizes regression models and accurately predicts employee salaries based on experience, previous CTC, and job roles, promoting fair salary structures and optimizing resource allocation for streamlined HR operations.

Ensemble-based, size-agnostic wrapper for the TabPFN classifier

A collection of AI and ML projects demonstrating various techniques, algorithms, and applications.

pyEnGNet: optimized reconstruction of gene co-expression networks using multi-GPU

CoNSEnsX - Complience of NMR-derived Structural Ensembles with Experimental Data

a personalized, offline, imaginary social media feed

Merlin Systems provides tools for combining recommendation models with other elements of production recommender systems (like feature stores, nearest neighbor search, and exploration strategies) into end-to-end recommendation pipelines that can be served with Triton Inference Server.

Development directory for Mixture of Large Language Models (MLLM) Project

Kubernetes operator to deploy ensembles of HPC applications 🍂️ (under development)

Multi-view hierarchical clustering in R

Performing and deploying clustering algorithm on an unsupervised dataset

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

an LLM toolkit

perturbation of coupled model input over a space of input variables