ml-lab Goto Github PK

inplace_abn

In-Place Activated BatchNorm for Memory-Optimized Training of DNNs

insightface

Face Recognition Project on MXnet

insightface_tf

Insight Face on TensorFlow

instacart-basket-prediction

Kaggle | Instacart Market Basket Analysis🥕🥉

instagan

PyTorch implementation of "InstaGAN: Instance-aware Image Translation" (ICLR 2019)

instant-ngp

Instant neural graphics primitives: lightning fast NeRF and more

interactive-deep-colorization

Real-Time User-Guided Image Colorization with Learned Deep Priors

interactive-hiphop

interpretable-machine-learning-with-python

Interpretable Machine Learning with Python, published by Packt

interpretable-ml-book

Book about interpretable machine learning

interpretable-test

Interpretable nonparameteric two-sample test

interpretablecnn

interpretablestrategydiscovery

intrinsic-dimension

introgressionbrowser

Introgression browser: high-throughput whole-genome SNP visualization doi: 10.1111/tpj.12800

inverse-reinforcement-learning

Implementations of selected inverse reinforcement learning algorithms.

investing

Investing Returns on the Market as a Whole

invoicenet

Deep neural network to extract intelligent information from invoice documents.

iris-2

Transformers are Sample Efficient World Models

irregulartimeseriesautoencoderpaper

is13

RNN for Spoken Language Understanding

isbi-2012

Image Segmentation Techniques on the ISBI 2012 dataset: http://brainiac2.mit.edu/isbi_challenge/

isda-for-deep-networks

isketchnfill

Software that can autocomplete sketches as the user starts drawing.

ismir2016

Deep Convolutional Networks on the Pitch Spiral for Musical Instrument Recognition

iter-reason

Code for Iterative Reasoning Paper (CVPR 2018)

iterative_inference

Implementation of iterative inference in deep latent variable models

iterdet

IterDet: Iterative Scheme for Object Detection in Crowded Environments

itl-ae

Information Theoretic Learning Auto-encoders

iv2018-hierarchical-semantic-segmentation-for-heterogeneous-datasets

Datasets and code for reproducing results for IV2018 paper "Training of Convolutional Networks on Multiple Heterogeneous Datasets for Street Scene Semantic Segmentation".