Popular GitHub Repositories for Amortized Sampling

A procedural Blender pipeline for photorealistic training image generation

LightSeq: A High Performance Library for Sequence Processing and Generation

Official code for "DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps" (Neurips 2022 Oral)

:dart: Task-oriented embedding tuning for BERT, CLIP, etc.

:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions

Boltzmann Machines in TensorFlow with examples

基于Pytorch和torchtext的自然语言处理深度学习框架。

Pool-based active learning in Python

Simple and readable code for training and sampling from diffusion models

A Python library for amortized Bayesian workflows using generative neural networks.

Verbalized Sampling, a training-free prompting strategy to mitigate mode collapse in LLMs by requesting responses with probabilities. Achieves 2-3x diversity improvement while maintaining quality. Model-agnostic framework with CLI/API for creative writing, synthetic data generation, and dialogue simulation.

PyTorch Implementation for Deep Metric Learning Pipelines

The official PyTorch implementation of the paper "SAITS: Self-Attention-based Imputation for Time Series". A fast and state-of-the-art (SOTA) deep-learning neural network model for efficient time-series imputation (impute multivariate incomplete time series containing NaN missing data/values with machine learning). https://arxiv.org/abs/2202.08516

Differentiable Point Cloud Sampling (CVPR 2020 Oral)

Official Repository of the paper "Trajectory Consistency Distillation"

?A curated list of Awesome Diffusion Inference Papers with Codes: Sampling, Cache, Quantization, Parallelism, etc.?

Synthetic Minority Over-Sampling Technique for Regression

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

Neural Network-Boosted Importance Nested Sampling for Bayesian Statistics

The Noise Contrastive Estimation for softmax output written in Pytorch