"Deep Generative Modeling": Introductory Examples

(CVPR 2021 Oral) Open World Object Detection

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

Boltzmann Machines in TensorFlow with examples

[ECCV 2022] Compositional Generation using Diffusion Models

Collecting research materials on energy/entropy based models

The purpose of this repository is to make prototypes as case study in the context of proof of concept(PoC) and research and development(R&D) that I have written in my website. The main research topics are Auto-Encoders in relation to the representation learning, the statistical machine learning for energy-based models, adversarial generation networks(GANs), Deep Reinforcement Learning such as Deep Q-Networks, semi-supervised learning, and neural network language model for natural language processing.

Code for reproducing results in the sliced score matching paper (UAI 2019)

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

[NeurIPS 2022] (Amortized) distributional control for pre-trained generative models

A PyTorch implementation of Implicit Behavioral Cloning

Official implementation of "Energy-Based Models for Deep Probabilistic Regression" (ECCV 2020) and "How to Train Your Energy-Based Model for Regression" (BMVC 2020).

[NeurIPS 2021 Spotlight] Learning to Compose Visual Relations

A framework for training energy-based diffusion models for sampling and energy estimation.

[AAAI 2022] Official Implementation of Active Learning for Domain Adaptation: An Energy-based Approach https://arxiv.org/abs/2112.01406

Extreme Q-Learning: Max Entropy RL without Entropy

[ICCV 2023] Unsupervised Compositional Concepts Discovery with Text-to-Image Generative Models

🍓 Build and train energy-based and diffusion models in PyTorch ⚡.

[CVPR 2024] TEA: Test-time Energy Adaptation

[ICML 2022] Latent Diffusion Energy-Based Model for Interpretable Text Modeling

Code for Weakly Supervised Energy-Based Learning for Action Segmentation (ICCV 2019 Oral)

Ying Nian Wu's UCLA Statistical Machine Learning Tutorial on generative modeling.

Official implementation of "Accurate 3D Object Detection using Energy-Based Models", CVPR Workshops 2021.

Some toy examples of score matching algorithms written in PyTorch

(CVPR 2022) Energy-based Latent Aligner for Incremental Learning

The official repository of "Energy-Based Cross Attention for Bayesian Context Update in Text-to-Image Diffusion Models".

[NeurIPS 2021] Unsupervised Foreground Extraction via Deep Region Competition

[NeurIPS 2024] Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow

ZeroC is a neuro-symbolic method that trained with elementary visual concepts and relations, can zero-shot recognize and acquire more complex, hierarchical concepts, even across domains

VectorDB library using dispersion models. Provides graph analysis, vector search and a energy-distribution stats for your vectors in one package.