atakehiro's Stars
labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
matterport/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
d2l-ai/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
thunlp/GNNPapers
Must-read papers on graph neural networks (GNN)
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
wandb/wandb
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
rapidsai/cudf
cuDF - GPU DataFrame Library
KevinMusgrave/pytorch-metric-learning
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
uber/causalml
Uplift modeling and causal inference with machine learning algorithms
rapidsai/cuml
cuML - RAPIDS Machine Learning Library
huawei-noah/Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
rasbt/machine-learning-book
Code Repository for Machine Learning with PyTorch and Scikit-Learn
shankarpandala/lazypredict
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
raminmh/liquid_time_constant_networks
Code Repository for Liquid Time-Constant Networks (LTCs)
tensorflow/similarity
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.
google-research/maxim
[CVPR 2022 Oral] Official repository for "MAXIM: Multi-Axis MLP for Image Processing". SOTA for denoising, deblurring, deraining, dehazing, and enhancement.
raminmh/CfC
Closed-form Continuous-time Neural Networks
BGU-CS-VIL/DeepDPM
"DeepDPM: Deep Clustering With An Unknown Number of Clusters" [Ronen, Finder, and Freifeld, CVPR 2022]
NVIDIA-Merlin/dataloader
The merlin dataloader lets you rapidly load tabular data for training deep leaning models with TensorFlow, PyTorch or JAX
lahoud/3d-vision-transformers
A list of 3D computer vision papers with Transformers
pynapple-org/pynapple
PYthon Neural Analysis Package :pineapple:
basiralab/GNNs-in-Network-Neuroscience
A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.
MouseLand/facemap
Framework for predicting neural activity from mouse orofacial movements tracked using a pose estimation model. Package also includes singular value decomposition (SVD) of behavioral videos.
ml-jku/DeepRC
DeepRC: Immune repertoire classification with attention-based deep massive multiple instance learning
neuroethology/TREBA
Learning trajectory representations using self-supervision and programmatic supervision.
neuroethology/MARS
End-user version of the Mouse Action Recognition System (MARS)
MIT-LCP/physionet-build
The new PhysioNet platform.
porteralab/EZcalcium
Calcium Data Extraction and Analysis
wanglabtongji/CCI
Evaluation of cell-cell interaction methods by integrating single-cell RNA sequencing data with spatial information