christina-winkler

christina-winkler's Stars

• VishalJ99/symbolic_distillation

  Symbolic distillation of Neural Networks using SR

  Language:Python4

• CompVis/fm-boosting

  FMBoost: Boosting Latent Diffusion with Flow Matching (ECCV 2024 Oral)

  Language:Python1823

• Doubiiu/ToonCrafter

  [SIGGRAPH Asia 2024, Journal Track] ToonCrafter: Generative Cartoon Interpolation

  Language:Python5.3k440

• optuna/optuna

  A hyperparameter optimization framework

  Language:Python10.8k1k

• tgwoodcock/convmag

  Conversion between units used in magnetism

  Language:Python3

• facebookresearch/nougat

  Implementation of Nougat Neural Optical Understanding for Academic Documents

  Language:Python8.9k568

• google-deepmind/jraph

  A Graph Neural Network Library in Jax

  Language:Python1.4k89

• mims-harvard/GraphXAI

  GraphXAI: Resource to support the development and evaluation of GNN explainers

  Language:Python16829

• zfjsail/gae-pytorch

  Graph Auto-Encoder in PyTorch

  Language:Python41379

• christina-winkler/clim-var-ds-cnf

  This repository contains the code for climate variable downscaling using conditional normalizing flows. Work done during internship @ MILA AI Research. 🛰️

  Language:Jupyter Notebook31

• hazdzz/awesome-gnn

  A list for GNNs and related works.

  809

• robbiewatt1/ClimateDiffuse

  Diffusion for climate downscaling

  Language:Python357

• CambridgeCIA/LION

  Learned Iterative Optimization Networks

  Language:Python1914

• Namkyeong/PolySRL_AI4Science

  The official source code for "Stoichiometry Representation Learning with Polymorphic Crystal Structures"

  Language:Python10

• yccyenchicheng/SegVAE

  Implementation of ECCV 2020 paper: "Controllable Image Synthesis via SegVAE". Project page: https://yccyenchicheng.github.io/SegVAE/. Paper: https://arxiv.org/abs/2007.08397.

  Language:Python535

• adarshraghunath/CDISR

  Conditional Diffusion model for 2D Image Super-Resolution(SR). Targets medical images and is inspired from SR3.

  Language:Python4

• alexhernandezgarcia/gflownet

  Generative Flow Networks - GFlowNet

  Language:Python18214

• CVxTz/IntegratedGradientsPytorch

  Integrated gradients attribution method implemented in PyTorch

  Language:Python245

• lanl/vision_transformers_explained

  This folder of code contains code and notebooks to supplement the "Vision Transformers Explained" series published on Towards Data Science written by Skylar Callis.

  Language:Jupyter Notebook6016

• vislearn/FrEIA

  Framework for Easily Invertible Architectures

  Language:Python767112

• benmoseley/AISE-2024

  ETH Zürich AI in the Sciences and Engineering Master's course 2024

  Language:Jupyter Notebook232

• exoplanet-dev/jaxoplanet

  Astronomical time series analysis with JAX

  Language:Python3612

• microsoft/torchgeo

  TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data

  Language:Python2.7k339

• AspirinCode/papers-for-molecular-design-using-DL

  List of Molecular and Material design using Generative AI and Deep Learning

  67097

• YorkUCVIL/Wavelet-Flow

  Wavelet Flow: Fast Training of High Resolution Normalizing Flows

  Language:Python592

• ixsluo/cond-cdvae

  An SE(3)-invariant autoencoder for generating the periodic structure of materials [ICLR 2022]

  Language:Python113

• ecmwf/climetlab

  Python package for easy access to weather and climate data

  Language:Python37458

• divelab/AIRS

  Artificial Intelligence Research for Science (AIRS)

  Language:Python51459

• xchhuang/simple-pytorch-3dgan

  A simple and unofficial 3D-GAN implementation using PyTorch [NeurIPS 2016]

  Language:Python8632

• black0017/3D-GAN-pytorch

  Responsible implementation of 3D-GAN NIPS 2016 paper:Learning a Probabilistic Latent Space of ObjectShapes via 3D Generative-Adversarial Modeling,that can be found https://papers.nips.cc/paper/6096-learning-a-probabilistic-latent-space-of-object-shapes-via-3d-generative-adversarial-modeling.pdf

  Language:Jupyter Notebook15423