alexandrahotti's Stars
Lagergren-Lab/MixtureVAEs
Repo for reproduction of the paper "Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational Autoencoders"
rasbt/LLM-workshop-2024
A 4-hour coding workshop to understand how LLMs are implemented and used
huggingface/local-gemma
Gemma 2 optimized for your local machine.
alexandrahotti/efficient-mixtures
Code for reproducing results for "Efficient Mixture Learning in Black-Box VI"
OSU-NLP-Group/Mind2Web
[NeurIPS'23 Spotlight] "Mind2Web: Towards a Generalist Agent for the Web"
OSU-NLP-Group/SeeAct
[ICML'24] SeeAct is a system for generalist web agents that autonomously carry out tasks on any given website, with a focus on large multimodal models (LMMs) such as GPT-4V(ision).
OpenGVLab/InternVL
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的可商用开源多模态对话模型
Alfred-N/IP-CAE
Indirectly Parameterized Concrete Autoencoders
klarna/product-page-dataset
dbuezas/biotic-text
karpathy/pytorch-normalizing-flows
Normalizing flows in PyTorch. Current intended use is education not production.
blei-lab/ars-reparameterization
Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
jluttine/tikz-bayesnet
TikZ library for drawing Bayesian networks, graphical models and (directed) factor graphs in LaTeX.
kevalmorabia97/CoVA-Web-Object-Detection
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
gemoran/sparse-vae-code
wgrathwohl/GWG_release
Official release of code for "Oops I Took A Gradient: Scalable Sampling for Discrete Distributions"
aiwabdn/pygln
Python implementation of GLN in different frameworks
wengong-jin/icml18-jtnn
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)
adjidieng/ETM
Topic Modeling in Embedding Spaces
deepfindr/gvae
physhik/Study-of-David-Mackay-s-book-
David Mackay's book review and problem solvings and own python codes, mathematica files
bayesgroup/deepbayes-2019
Practical assignments of the Deep|Bayes summer school 2019
awesome-mlss/awesome-mlss
🤖 Machine Learning Summer School deadlines
alirezamika/autoscraper
A Smart, Automatic, Fast and Lightweight Web Scraper for Python
zhengqigao/PRML-Solution-Manual
My Own Solution Manual of PRML
sjhwang82/AdvancedML
Reading list for the Advanced Machine Learning Course
mattiasvillani/AdvBayesLearnCourse
Course material for the PhD course in Advanced Bayesian Learning
bayesiains/nflows
Normalizing flows in PyTorch
ermongroup/cs228-notes
Course notes for CS228: Probabilistic Graphical Models.
mattiasvillani/BayesLearnCourse
Bayesian Learning course at Stockholm University