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deep_autoviml

Build tensorflow keras model pipelines in a single line of code. Created by Ram Seshadri. Collaborators welcome. Permission granted upon request.

deeppavlov-1

deepphonemizer

Grapheme to phoneme conversion with deep learning.

deeppurpose

A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)

deepsparse

Neural network inference engine that delivers GPU-class performance for sparsified models on CPUs

deepspeech.pytorch

Speech Recognition using DeepSpeech2.

deepspeed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

deepspeed-mii

deepspeedexamples

Example models using DeepSpeed

deepsvg

[NeurIPS 2020] Official code for the paper "DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation". Includes a PyTorch library for deep learning with SVG data.

deepxml

Implementation of DeepXML

deepy

Deepy is a free, open-source Multiskill AI Assistant built using DeepPavlov Conversational AI Stack. It is built on top of DeepPavlov Agent running as container in Docker. It runs on x86_64 machines, and prefers having NVIDIA GPUs on the machine.

deformable-detr

Deformable DETR: Deformable Transformers for End-to-End Object Detection.

deidentify

A Python library to de-identify medical records with state-of-the-art NLP methods.

deis

DEIS: Fast Sampling of Diffusion Models with Exponential Integrator

deit-tf

About Includes PyTorch -> Keras model porting code for DeiT models with fine-tuning and inference notebooks.

delpher-lm

Language Model for Historic Dutch (Delpher Corpus)

delta

DELTA is a deep learning based natural language and speech processing platform.

deluxo_adjacency

denoiser

Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a causal speech enhancement model working on the raw waveform that runs in real-time on a laptop CPU. The proposed model is based on an encoder-decoder architecture with skip-connections. It is optimized on both time and frequency domains, using multiple loss functions. Empirical evidence shows that it is capable of removing various kinds of background noise including stationary and non-stationary noises, as well as room reverb. Additionally, we suggest a set of data augmentation techniques applied directly on the raw waveform which further improve model performance and its generalization abilities.

denoising-diffusion-flax

Implementing the Denoising Diffusion Probabilistic Model in Flax

denoising-diffusion-pytorch

Implementation of Denoising Diffusion Probabilistic Model in Pytorch

denoising-diffusion-pytorch-1

Implementation of Denoising Diffusion Probabilistic Models in PyTorch

dense

A toolkit for building dense retrievers with deep language models.

dense-retrieval

densedepth

High Quality Monocular Depth Estimation via Transfer Learning

densephrases

ACL'2021: Learning Dense Representations of Phrases at Scale; EMNLP'2021: Phrase Retrieval Learns Passage Retrieval, Too

deoldify

A Deep Learning based project for colorizing and restoring old images (and video!)

dependency-parser

依存句法解析

deploy-deep-learning-models-tf-serving-docker

Official repository of "TensorFlow Serving with Docker for Model Deployment" Coursera Project