Models and examples built with TensorFlow

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…

A python library for user-friendly forecasting and anomaly detection on time series.

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

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

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

Probabilistic time series modeling in Python

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

FFCV: Fast Forward Computer Vision (and other ML workloads!)

A simple tool to update bib entries with their official information (e.g., DBLP or the ACL anthology).

Real time transcription with OpenAI Whisper.

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputatio…

Synchronized Batch Normalization implementation in PyTorch.

SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

A novel Multimodal Large Language Model (MLLM) architecture, designed to structurally align visual and textual embeddings.

PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend

Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.

❄️🔥 Visual Prompt Tuning [ECCV 2022] https://arxiv.org/abs/2203.12119

Research on Tabular Deep Learning: Papers & Packages

PyCIL: A Python Toolbox for Class-Incremental Learning

a pytorch lib with state-of-the-art architectures, pretrained models and real-time updated results

Pytorch implementation for "Large-Scale Long-Tailed Recognition in an Open World" (CVPR 2019 ORAL)

The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.

Unofficial PyTorch implementation of "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence"

A comprehensive toolkit and benchmark for tabular data learning, featuring 35+ deep methods, more than 10 classical methods, and 300 diverse tabular datasets.

Repository for Kuzushiji-MNIST, Kuzushiji-49, and Kuzushiji-Kanji

[NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss