Popular GitHub Repositories for Mutual Funds

Rethinking Image Inpainting via a Mutual Encoder Decoder with Feature Equalizations. ECCV 2020 Oral

A pytorch implementation of MINE(Mutual Information Neural Estimation)

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

Smart Algorithms to predict buying and selling of stocks on the basis of Mutual Funds Analysis, Stock Trends Analysis and Prediction, Portfolio Risk Factor, Stock and Finance Market News Sentiment Analysis and Selling profit ratio. Project developed as a part of NSE-FutureTech-Hackathon 2018, Mumbai. Team : Semicolon

Diffusion and Mutual Information-Based Target Speaker SVS by Learning from Singing Teacher

Speech Representation Disentanglement with Adversarial Mutual Information Learning for One-shot Voice Conversion (Interspeech 2022)

Graph Representation Learning via Graphical Mutual Information Maximization

Code base for M3DeTR: Multi-representation, Multi-scale, Mutual-relation 3D Object Detection with Transformers

[IJCAI 2024]Official PyTorch Implementation of Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion

This is the official repository for our CVPR 2023 paper 'Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification'.

Pytorch implementation of Learning Disentangled Representations via Mutual Information Estimation (ECCV 2020)

[WSDM 2021]Bipartite Graph Embedding via Mutual Information Maximization

An Unsupervised Sentence Embedding Method by Mutual Information Maximization (EMNLP2020)

This clustering based anomaly detection project implements unsupervised clustering algorithms on the NSL-KDD and IDS 2017 datasets

Investigate how mutual funds leverage credit derivatives by studying their routine filings to the SEC using NLP techniques ??

Code for GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation (SIGIR 2020)

Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extraction, feature selection. CNN-based and extensive machine learning techniques were then applied for fault detection.

[Paper][ICLR 2025] Mixture of Modality Knowledge Experts for Robust Multi-modal Knowledge Graph Completion

Cross-Modality Mutual Learning for Smart Contract Vulnerability Detection

A Python package for efficient optimisation of real-space renormalization group transformations using Tensorflow.