A highly efficient implementation of Gaussian Processes in PyTorch

Bayesian optimization in PyTorch

The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.

Conditional GAN for generating synthetic tabular data.

Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.

1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.

Uniform Manifold Approximation and Projection

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

DeepTables: Deep-learning Toolkit for Tabular data

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …

Sequential model-based optimization with a `scipy.optimize` interface

Approaching (Almost) Any Machine Learning Problem

Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.

Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.

Instant neural graphics primitives: lightning fast NeRF and more

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

A collection of resources and papers on Diffusion Models

Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts

A playbook for systematically maximizing the performance of deep learning models.

Benchmarking large language models' complex reasoning ability with chain-of-thought prompting

Development repository for the Triton language and compiler

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