ML-University VS Awesome-Diffusion-Models

Compare ML-University vs Awesome-Diffusion-Models and see what are their differences.

ML-University

Machine Learning Open Source University (by d0r1h)
Machine Learning open-source University Artificial intelligence Learning awsome awsome-list Free Deep Learning Natural Language Processing Mathematics Course computer-science Data Science reinforcement-learning neural-network
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Awesome-Diffusion-Models

A collection of resources and papers on Diffusion Models (by diff-usion)
diffusion-models generative-model Machine Learning score-matching Artificial intelligence score-based
Source Code
diff-usion.github.io
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ML-University Awesome-Diffusion-Models
6 6
794 10,064
- -
3.4 6.1
7 months ago 2 months ago
HTML HTML
- MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ML-University

Posts with mentions or reviews of ML-University. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-07-20.

Awesome-Diffusion-Models

Posts with mentions or reviews of Awesome-Diffusion-Models. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-10.

What are some alternatives?

When comparing ML-University and Awesome-Diffusion-Models you can also consider the following projects:

ai-deadlines - :alarm_clock: AI conference deadline countdowns

denoising-diffusion-pytorch - Implementation of Denoising Diffusion Probabilistic Model in Pytorch

overlays - MarketerBay Overlays. Sandbox open source projects.

Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch - [ECCV 2022] Compositional Generation using Diffusion Models

human-memory - Course materials for Dartmouth course: Human Memory (PSYC 51.09)

dalle-mini - DALL·E Mini - Generate images from a text prompt

golang-training - Golang for Backend Developer with Nordic Coder

papers-I-read - A-Paper-A-Week

CS7038-Malware-Analysis - Course Repository for University of Cincinnati Malware Analysis Class (CS[567]038)

MachineLearning-BaseballPrediction-BlazorApp - Machine Learning over historical baseball data using latest Microsoft AI & Development technology stack (.Net Core & Blazor)

Recognition-of-logical-document-structures - First approach for recognizing logical document structures like texts, sentences, segments, words, chars and sentence/segment depth based on recurrent neural network grammars.

CogView2 - official code repo for paper "CogView2: Faster and Better Text-to-Image Generation via Hierarchical Transformers"

ML-University vs ai-deadlines Awesome-Diffusion-Models vs denoising-diffusion-pytorch ML-University vs overlays Awesome-Diffusion-Models vs Compositional-Visual-Generation-with-Composable-Diffusion-Models-PyTorch ML-University vs human-memory Awesome-Diffusion-Models vs dalle-mini ML-University vs golang-training Awesome-Diffusion-Models vs papers-I-read ML-University vs CS7038-Malware-Analysis Awesome-Diffusion-Models vs MachineLearning-BaseballPrediction-BlazorApp ML-University vs Recognition-of-logical-document-structures Awesome-Diffusion-Models vs CogView2