Popular GitHub Repositories for Variable Elimination

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

GIF is a photorealistic generative face model with explicit 3D geometric and photometric control.

DGMs for NLP. A roadmap.

Official implementation of "DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents"

Pytorch Implementation of our ACL 2020 Paper "Reasoning with Latent Structure Refinement for Document-Level Relation Extraction"

End-to-end variable length Captcha recognition using CNN+RNN+Attention/CTC (pytorch implementation). 端到端的不定长验证码识别

SurvSHAP(t): Time-dependent explanations of machine learning survival models

LVCNet: Efficient Condition-Dependent Modeling Network for Waveform Generation

Official implementation of the paper Stochastic Latent Residual Video Prediction

Bayesian Methods for Machine Learning

[Paperlist] Awesome paper list of controllable text generation via latent auto-encoders. Contributions of any kind are welcome.

Neural State-Space Models and Latent Dynamics Functions in PyTorch for High-Dimensional Forecasting

Generative Query Network for rendering 3D scenes from 2D images

Official implementation of our ECCV paper "StretchBEV: Stretching Future Instance Prediction Spatially and Temporally"

This is a lightweight GAN developed for real-time deblurring. The model has a super tiny size and a rapid inference time. The motivation is to boost marker detection in robotic applications, however, you may use it for other applications definitely.

Official implementation of NeurIPS'22 paper "Monte Carlo Tree Search based Variable Selection for High-Dimensional Bayesian Optimization"

SLAMP: Stochastic Latent Appearance and Motion Prediction

Re-implementation and extension of the work described in "Learning to Represent Programs with Graphs"

VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning

Official Implementation of SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks