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Repository for "Differentiable Causal Discovery from Interventional Data"
A General Causal Inference Framework by Encoding Generative Modeling
Gene expression time-series extrapolation for heterogeneous data
Regulatory Temporal Interaction Network Inference
TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics
Causal Effect Inference with Deep Latent-Variable Models
This repository implements Variational Causal Inference (VCI), a variational Bayesian causal inference framework for high-dimensional treatment effect predictions and estimations.
A deep learning architecture for robust inference and accurate prediction of cellular dynamics
🌟 Wiki of OI / ICPC for everyone. （某大型游戏线上攻略，内含炫酷算术魔法）
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
This is a repo for Neural ODE and CDE forecasters.
An easy/swift-to-adapt PyTorch-Lighting template. 套壳模板，简单易用，稍改原来Pytorch代码，即可适配Lightning。You can translate your previous Pytorch code much easier using this template, and keep your freedom to edit a…
【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容
DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks
https://www.sc-best-practices.org
The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell level. CPA performs OOD predictions of unseen combinations of dr…
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀
An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
Machine Learning and Artificial Intelligence for Medicine.