699 Open source projects that are alternatives of or similar to Dalle Mtf

Variational autoencoder for Lego minifig faces

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Experiments with Adversarial Autoencoders using Keras

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

Variational autoencoder, denoising autoencoder and other variations of autoencoders implementation in keras

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

API of Articut 中文斷詞 (兼具語意詞性標記)：「斷詞」又稱「分詞」，是中文資訊處理的基礎。Articut 不用機器學習，不需資料模型，只用現代白話中文語法規則，即能達到 SIGHAN 2005 F1-measure 94% 以上，Recall 96% 以上的成績。

PyTorch implementation of normalizing flow models

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits

MorphL Community Edition uses big data and machine learning to predict user behaviors in digital products and services with the end goal of increasing KPIs (click-through rates, conversion rates, etc.) through personalization

Timbre transfer with variational autoencoding and cycle-consistent adversarial networks. Able to transfer the timbre of an audio source to that of another.

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

A dataset of millions of news articles scraped from a curated list of data sources.

Text Variational Autoencoder inspired by the paper 'Generating Sentences from a Continuous Space' Bowman et al. https://arxiv.org/abs/1511.06349

Variational Neural Machine Translation System

Implementation of a convolutional Variational-Autoencoder model in pytorch.

🦄 An Artificial Inteligence to teach Google's Dinosaur to jump cactus

Assessing Generative Models via Precision and Recall (official repository)

Learning about Haskell with Variational Autoencoders

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

An Introduction to Deep Generative Modeling: Examples

No description or website provided.

A PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)

Implementation of 'Self-Adversarial Variational Autoencoder with Gaussian Anomaly Prior Distribution for Anomaly Detection'

A review of change detection methods, including codes and open data sets for deep learning. From paper: change detection based on artificial intelligence: state-of-the-art and challenges.

VAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.

Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch

🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.

CVAE_XGate model in paper "Xu, Dusek, Konstas, Rieser. Better Conversations by Modeling, Filtering, and Optimizing for Coherence and Diversity"

Code for our paper -- Hyperprior Induced Unsupervised Disentanglement of Latent Representations (AAAI 2019)

Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)

An on-premises, bare-metal solution for deploying GPU-powered applications in containers

Open-source code for our paper: Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition

Lagrangian VAE

Invariant representation learning from imaging and spectral data

Pytorch implementation of Hyperspherical Variational Auto-Encoders

Torch Implemention of ECCV'16 paper: Attribute2Image

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

No description or website provided.

An Open Source, Self-Hosted Platform For Applied Deep Learning Development

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

We got a stew going!

Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution

PyTorch implementation of a VAE-based generative classifier, as well as other class-incremental learning methods that do not store data (DGR, BI-R, EWC, SI, CWR, CWR+, AR1, the "labels trick", SLDA).

Using neural network to build expressive hierarchical distribution; A variational method to accurately estimate posterior uncertainty; A fast and general method for Bayesian inference. (ICML 2018)

AE and VAE Playground in PyTorch

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

An implementation of VAEGAN (variational autoencoder + generative adversarial network).

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

music generation with a classifying variational autoencoder (VAE) and LSTM

Variational autoencoder for anomaly detection (in PyTorch).

Machine Learning Platform for Kubernetes (MLOps tools for experimentation and automation)

Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.

TextBox is an open-source library for building text generation system.

CALC2.0: Combining Appearance, Semantic and Geometric Information for Robust and Efficient Visual Loop Closure

Shared Latent Space VAE's