Big GCVAE: Probabilistic Graphical BERT-GPT2 Transformer Model for Failure Analysis Triplet Generation

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

This repository contains demos I made with the Transformers library by HuggingFace.

PyTorch code and models for V-JEPA self-supervised learning from video.

Forecast stock prices using machine learning approach. A time series analysis. Employ the Use of Predictive Modeling in Machine Learning to Forecast Stock Return. Approach Used by Hedge Funds to Se…

A curated list of Best Artificial Intelligence Resources

12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

The simplest, fastest repository for training/finetuning medium-sized GPTs.

Inference code for Llama models

Optimus: the first large-scale pre-trained VAE language model

Useful extra functionality for TensorFlow 2.x maintained by SIG-addons

disentanglement_lib is an open-source library for research on learning disentangled representations.

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristi…

Laplace approximations for Deep Learning.

Decentralized Reinforcment Learning: Global Decision-Making via Local Economic Transactions (ICML 2020)

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Minimum-distortion embedding with PyTorch

Must-read papers on graph neural networks (GNN)

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

A very simple framework for state-of-the-art Natural Language Processing (NLP)

A library for efficient similarity search and clustering of dense vectors.

GPT-3: Language Models are Few-Shot Learners

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

A curated list of gradient boosting research papers with implementations.

A curated list of community detection research papers with implementations.

Bioinformatics 2020: Graph Neural Networks for DNA Sequence Classification

High-quality implementations of standard and SOTA methods on a variety of tasks.

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)